An articulatorily constrained, maximum entropy approach to speech recognition and speech coding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogden, J.

Hidden Markov models (HMM`s) are among the most popular tools for performing computer speech recognition. One of the primary reasons that HMM`s typically outperform other speech recognition techniques is that the parameters used for recognition are determined by the data, not by preconceived notions of what the parameters should be. This makes HMM`s better able to deal with intra- and inter-speaker variability despite the limited knowledge of how speech signals vary and despite the often limited ability to correctly formulate rules describing variability and invariance in speech. In fact, it is often the case that when HMM parameter values aremore » constrained using the limited knowledge of speech, recognition performance decreases. However, the structure of an HMM has little in common with the mechanisms underlying speech production. Here, the author argues that by using probabilistic models that more accurately embody the process of speech production, he can create models that have all the advantages of HMM`s, but that should more accurately capture the statistical properties of real speech samples--presumably leading to more accurate speech recognition. The model he will discuss uses the fact that speech articulators move smoothly and continuously. Before discussing how to use articulatory constraints, he will give a brief description of HMM`s. This will allow him to highlight the similarities and differences between HMM`s and the proposed technique.« less

Address entry while driving: speech recognition versus a touch-screen keyboard.

PubMed

Tsimhoni, Omer; Smith, Daniel; Green, Paul

2004-01-01

A driving simulator experiment was conducted to determine the effects of entering addresses into a navigation system during driving. Participants drove on roads of varying visual demand while entering addresses. Three address entry methods were explored: word-based speech recognition, character-based speech recognition, and typing on a touch-screen keyboard. For each method, vehicle control and task measures, glance timing, and subjective ratings were examined. During driving, word-based speech recognition yielded the shortest total task time (15.3 s), followed by character-based speech recognition (41.0 s) and touch-screen keyboard (86.0 s). The standard deviation of lateral position when performing keyboard entry (0.21 m) was 60% higher than that for all other address entry methods (0.13 m). Degradation of vehicle control associated with address entry using a touch screen suggests that the use of speech recognition is favorable. Speech recognition systems with visual feedback, however, even with excellent accuracy, are not without performance consequences. Applications of this research include the design of in-vehicle navigation systems as well as other systems requiring significant driver input, such as E-mail, the Internet, and text messaging.

Evaluation of Speech Recognition of Cochlear Implant Recipients Using Adaptive, Digital Remote Microphone Technology and a Speech Enhancement Sound Processing Algorithm.

PubMed

Wolfe, Jace; Morais, Mila; Schafer, Erin; Agrawal, Smita; Koch, Dawn

2015-05-01

Cochlear implant recipients often experience difficulty with understanding speech in the presence of noise. Cochlear implant manufacturers have developed sound processing algorithms designed to improve speech recognition in noise, and research has shown these technologies to be effective. Remote microphone technology utilizing adaptive, digital wireless radio transmission has also been shown to provide significant improvement in speech recognition in noise. There are no studies examining the potential improvement in speech recognition in noise when these two technologies are used simultaneously. The goal of this study was to evaluate the potential benefits and limitations associated with the simultaneous use of a sound processing algorithm designed to improve performance in noise (Advanced Bionics ClearVoice) and a remote microphone system that incorporates adaptive, digital wireless radio transmission (Phonak Roger). A two-by-two way repeated measures design was used to examine performance differences obtained without these technologies compared to the use of each technology separately as well as the simultaneous use of both technologies. Eleven Advanced Bionics (AB) cochlear implant recipients, ages 11 to 68 yr. AzBio sentence recognition was measured in quiet and in the presence of classroom noise ranging in level from 50 to 80 dBA in 5-dB steps. Performance was evaluated in four conditions: (1) No ClearVoice and no Roger, (2) ClearVoice enabled without the use of Roger, (3) ClearVoice disabled with Roger enabled, and (4) simultaneous use of ClearVoice and Roger. Speech recognition in quiet was better than speech recognition in noise for all conditions. Use of ClearVoice and Roger each provided significant improvement in speech recognition in noise. The best performance in noise was obtained with the simultaneous use of ClearVoice and Roger. ClearVoice and Roger technology each improves speech recognition in noise, particularly when used at the same time. Because ClearVoice does not degrade performance in quiet settings, clinicians should consider recommending ClearVoice for routine, full-time use for AB implant recipients. Roger should be used in all instances in which remote microphone technology may assist the user in understanding speech in the presence of noise. American Academy of Audiology.

Audibility-based predictions of speech recognition for children and adults with normal hearing.

PubMed

McCreery, Ryan W; Stelmachowicz, Patricia G

2011-12-01

This study investigated the relationship between audibility and predictions of speech recognition for children and adults with normal hearing. The Speech Intelligibility Index (SII) is used to quantify the audibility of speech signals and can be applied to transfer functions to predict speech recognition scores. Although the SII is used clinically with children, relatively few studies have evaluated SII predictions of children's speech recognition directly. Children have required more audibility than adults to reach maximum levels of speech understanding in previous studies. Furthermore, children may require greater bandwidth than adults for optimal speech understanding, which could influence frequency-importance functions used to calculate the SII. Speech recognition was measured for 116 children and 19 adults with normal hearing. Stimulus bandwidth and background noise level were varied systematically in order to evaluate speech recognition as predicted by the SII and derive frequency-importance functions for children and adults. Results suggested that children required greater audibility to reach the same level of speech understanding as adults. However, differences in performance between adults and children did not vary across frequency bands. © 2011 Acoustical Society of America

Multitasking During Degraded Speech Recognition in School-Age Children

PubMed Central

Ward, Kristina M.; Brehm, Laurel

2017-01-01

Multitasking requires individuals to allocate their cognitive resources across different tasks. The purpose of the current study was to assess school-age children’s multitasking abilities during degraded speech recognition. Children (8 to 12 years old) completed a dual-task paradigm including a sentence recognition (primary) task containing speech that was either unprocessed or noise-band vocoded with 8, 6, or 4 spectral channels and a visual monitoring (secondary) task. Children’s accuracy and reaction time on the visual monitoring task was quantified during the dual-task paradigm in each condition of the primary task and compared with single-task performance. Children experienced dual-task costs in the 6- and 4-channel conditions of the primary speech recognition task with decreased accuracy on the visual monitoring task relative to baseline performance. In all conditions, children’s dual-task performance on the visual monitoring task was strongly predicted by their single-task (baseline) performance on the task. Results suggest that children’s proficiency with the secondary task contributes to the magnitude of dual-task costs while multitasking during degraded speech recognition. PMID:28105890

Multitasking During Degraded Speech Recognition in School-Age Children.

PubMed

Grieco-Calub, Tina M; Ward, Kristina M; Brehm, Laurel

2017-01-01

Multitasking requires individuals to allocate their cognitive resources across different tasks. The purpose of the current study was to assess school-age children's multitasking abilities during degraded speech recognition. Children (8 to 12 years old) completed a dual-task paradigm including a sentence recognition (primary) task containing speech that was either unprocessed or noise-band vocoded with 8, 6, or 4 spectral channels and a visual monitoring (secondary) task. Children's accuracy and reaction time on the visual monitoring task was quantified during the dual-task paradigm in each condition of the primary task and compared with single-task performance. Children experienced dual-task costs in the 6- and 4-channel conditions of the primary speech recognition task with decreased accuracy on the visual monitoring task relative to baseline performance. In all conditions, children's dual-task performance on the visual monitoring task was strongly predicted by their single-task (baseline) performance on the task. Results suggest that children's proficiency with the secondary task contributes to the magnitude of dual-task costs while multitasking during degraded speech recognition.

Age and measurement time-of-day effects on speech recognition in noise.

PubMed

Veneman, Carrie E; Gordon-Salant, Sandra; Matthews, Lois J; Dubno, Judy R

2013-01-01

The purpose of this study was to determine the effect of measurement time of day on speech recognition in noise and the extent to which time-of-day effects differ with age. Older adults tend to have more difficulty understanding speech in noise than younger adults, even when hearing is normal. Two possible contributors to this age difference in speech recognition may be measurement time of day and inhibition. Most younger adults are "evening-type," showing peak circadian arousal in the evening, whereas most older adults are "morning-type," with circadian arousal peaking in the morning. Tasks that require inhibition of irrelevant information have been shown to be affected by measurement time of day, with maximum performance attained at one's peak time of day. The authors hypothesized that a change in inhibition will be associated with measurement time of day and therefore affect speech recognition in noise, with better performance in the morning for older adults and in the evening for younger adults. Fifteen younger evening-type adults (20-28 years) and 15 older morning-type adults with normal hearing (66-78 years) listened to the Hearing in Noise Test (HINT) and the Quick Speech in Noise (QuickSIN) test in the morning and evening (peak and off-peak times). Time of day preference was assessed using the Morningness-Eveningness Questionnaire. Sentences and noise were presented binaurally through insert earphones. During morning and evening sessions, participants solved word-association problems within the visual-distraction task (VDT), which was used as an estimate of inhibition. After each session, participants rated perceived mental demand of the tasks using a revised version of the NASA Task Load Index. Younger adults performed significantly better on the speech-in-noise tasks and rated themselves as requiring significantly less mental demand when tested at their peak (evening) than off-peak (morning) time of day. In contrast, time-of-day effects were not observed for the older adults on the speech recognition or rating tasks. Although older adults required significantly more advantageous signal-to-noise ratios than younger adults for equivalent speech-recognition performance, a significantly larger younger versus older age difference in speech recognition was observed in the evening than in the morning. Older adults performed significantly poorer than younger adults on the VDT, but performance was not affected by measurement time of day. VDT performance for misleading distracter items was significantly correlated with HINT and QuickSIN test performance at the peak measurement time of day. Although all participants had normal hearing, speech recognition in noise was significantly poorer for older than younger adults, with larger age-related differences in the evening (an off-peak time for older adults) than in the morning. The significant effect of measurement time of day suggests that this factor may impact the clinical assessment of speech recognition in noise for all individuals. It appears that inhibition, as estimated by a visual distraction task for misleading visual items, is a cognitive mechanism that is related to speech-recognition performance in noise, at least at a listener's peak time of day.

Significance of parametric spectral ratio methods in detection and recognition of whispered speech

NASA Astrophysics Data System (ADS)

Mathur, Arpit; Reddy, Shankar M.; Hegde, Rajesh M.

2012-12-01

In this article the significance of a new parametric spectral ratio method that can be used to detect whispered speech segments within normally phonated speech is described. Adaptation methods based on the maximum likelihood linear regression (MLLR) are then used to realize a mismatched train-test style speech recognition system. This proposed parametric spectral ratio method computes a ratio spectrum of the linear prediction (LP) and the minimum variance distortion-less response (MVDR) methods. The smoothed ratio spectrum is then used to detect whispered segments of speech within neutral speech segments effectively. The proposed LP-MVDR ratio method exhibits robustness at different SNRs as indicated by the whisper diarization experiments conducted on the CHAINS and the cell phone whispered speech corpus. The proposed method also performs reasonably better than the conventional methods for whisper detection. In order to integrate the proposed whisper detection method into a conventional speech recognition engine with minimal changes, adaptation methods based on the MLLR are used herein. The hidden Markov models corresponding to neutral mode speech are adapted to the whispered mode speech data in the whispered regions as detected by the proposed ratio method. The performance of this method is first evaluated on whispered speech data from the CHAINS corpus. The second set of experiments are conducted on the cell phone corpus of whispered speech. This corpus is collected using a set up that is used commercially for handling public transactions. The proposed whisper speech recognition system exhibits reasonably better performance when compared to several conventional methods. The results shown indicate the possibility of a whispered speech recognition system for cell phone based transactions.

Increase in Speech Recognition Due to Linguistic Mismatch between Target and Masker Speech: Monolingual and Simultaneous Bilingual Performance

ERIC Educational Resources Information Center

Calandruccio, Lauren; Zhou, Haibo

2014-01-01

Purpose: To examine whether improved speech recognition during linguistically mismatched target-masker experiments is due to linguistic unfamiliarity of the masker speech or linguistic dissimilarity between the target and masker speech. Method: Monolingual English speakers (n = 20) and English-Greek simultaneous bilinguals (n = 20) listened to…

Histogram equalization with Bayesian estimation for noise robust speech recognition.

PubMed

Suh, Youngjoo; Kim, Hoirin

2018-02-01

The histogram equalization approach is an efficient feature normalization technique for noise robust automatic speech recognition. However, it suffers from performance degradation when some fundamental conditions are not satisfied in the test environment. To remedy these limitations of the original histogram equalization methods, class-based histogram equalization approach has been proposed. Although this approach showed substantial performance improvement under noise environments, it still suffers from performance degradation due to the overfitting problem when test data are insufficient. To address this issue, the proposed histogram equalization technique employs the Bayesian estimation method in the test cumulative distribution function estimation. It was reported in a previous study conducted on the Aurora-4 task that the proposed approach provided substantial performance gains in speech recognition systems based on the acoustic modeling of the Gaussian mixture model-hidden Markov model. In this work, the proposed approach was examined in speech recognition systems with deep neural network-hidden Markov model (DNN-HMM), the current mainstream speech recognition approach where it also showed meaningful performance improvement over the conventional maximum likelihood estimation-based method. The fusion of the proposed features with the mel-frequency cepstral coefficients provided additional performance gains in DNN-HMM systems, which otherwise suffer from performance degradation in the clean test condition.

Speech emotion recognition methods: A literature review

NASA Astrophysics Data System (ADS)

Basharirad, Babak; Moradhaseli, Mohammadreza

2017-10-01

Recently, attention of the emotional speech signals research has been boosted in human machine interfaces due to availability of high computation capability. There are many systems proposed in the literature to identify the emotional state through speech. Selection of suitable feature sets, design of a proper classifications methods and prepare an appropriate dataset are the main key issues of speech emotion recognition systems. This paper critically analyzed the current available approaches of speech emotion recognition methods based on the three evaluating parameters (feature set, classification of features, accurately usage). In addition, this paper also evaluates the performance and limitations of available methods. Furthermore, it highlights the current promising direction for improvement of speech emotion recognition systems.

Speech recognition in advanced rotorcraft - Using speech controls to reduce manual control overload

NASA Technical Reports Server (NTRS)

Vidulich, Michael A.; Bortolussi, Michael R.

1988-01-01

An experiment has been conducted to ascertain the usefulness of helicopter pilot speech controls and their effect on time-sharing performance, under the impetus of multiple-resource theories of attention which predict that time-sharing should be more efficient with mixed manual and speech controls than with all-manual ones. The test simulation involved an advanced, single-pilot scout/attack helicopter. Performance and subjective workload levels obtained supported the claimed utility of speech recognition-based controls; specifically, time-sharing performance was improved while preparing a data-burst transmission of information during helicopter hover.

Speech recognition systems on the Cell Broadband Engine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Y; Jones, H; Vaidya, S

In this paper we describe our design, implementation, and first results of a prototype connected-phoneme-based speech recognition system on the Cell Broadband Engine{trademark} (Cell/B.E.). Automatic speech recognition decodes speech samples into plain text (other representations are possible) and must process samples at real-time rates. Fortunately, the computational tasks involved in this pipeline are highly data-parallel and can receive significant hardware acceleration from vector-streaming architectures such as the Cell/B.E. Identifying and exploiting these parallelism opportunities is challenging, but also critical to improving system performance. We observed, from our initial performance timings, that a single Cell/B.E. processor can recognize speech from thousandsmore » of simultaneous voice channels in real time--a channel density that is orders-of-magnitude greater than the capacity of existing software speech recognizers based on CPUs (central processing units). This result emphasizes the potential for Cell/B.E.-based speech recognition and will likely lead to the future development of production speech systems using Cell/B.E. clusters.« less

Speech recognition in individuals with sensorineural hearing loss.

PubMed

de Andrade, Adriana Neves; Iorio, Maria Cecilia Martinelli; Gil, Daniela

2016-01-01

Hearing loss can negatively influence the communication performance of individuals, who should be evaluated with suitable material and in situations of listening close to those found in everyday life. To analyze and compare the performance of patients with mild-to-moderate sensorineural hearing loss in speech recognition tests carried out in silence and with noise, according to the variables ear (right and left) and type of stimulus presentation. The study included 19 right-handed individuals with mild-to-moderate symmetrical bilateral sensorineural hearing loss, submitted to the speech recognition test with words in different modalities and speech test with white noise and pictures. There was no significant difference between right and left ears in any of the tests. The mean number of correct responses in the speech recognition test with pictures, live voice, and recorded monosyllables was 97.1%, 85.9%, and 76.1%, respectively, whereas after the introduction of noise, the performance decreased to 72.6% accuracy. The best performances in the Speech Recognition Percentage Index were obtained using monosyllabic stimuli, represented by pictures presented in silence, with no significant differences between the right and left ears. After the introduction of competitive noise, there was a decrease in individuals' performance. Copyright © 2015 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.

Recognition of Speech from the Television with Use of a Wireless Technology Designed for Cochlear Implants.

PubMed

Duke, Mila Morais; Wolfe, Jace; Schafer, Erin

2016-05-01

Cochlear implant (CI) recipients often experience difficulty understanding speech in noise and speech that originates from a distance. Many CI recipients also experience difficulty understanding speech originating from a television. Use of hearing assistance technology (HAT) may improve speech recognition in noise and for signals that originate from more than a few feet from the listener; however, there are no published studies evaluating the potential benefits of a wireless HAT designed to deliver audio signals from a television directly to a CI sound processor. The objective of this study was to compare speech recognition in quiet and in noise of CI recipients with the use of their CI alone and with the use of their CI and a wireless HAT (Cochlear Wireless TV Streamer). A two-way repeated measures design was used to evaluate performance differences obtained in quiet and in competing noise (65 dBA) with the CI sound processor alone and with the sound processor coupled to the Cochlear Wireless TV Streamer. Sixteen users of Cochlear Nucleus 24 Freedom, CI512, and CI422 implants were included in the study. Participants were evaluated in four conditions including use of the sound processor alone and use of the sound processor with the wireless streamer in quiet and in the presence of competing noise at 65 dBA. Speech recognition was evaluated in each condition with two full lists of Computer-Assisted Speech Perception Testing and Training Sentence-Level Test sentences presented from a light-emitting diode television. Speech recognition in noise was significantly better with use of the wireless streamer compared to participants' performance with their CI sound processor alone. There was also a nonsignificant trend toward better performance in quiet with use of the TV Streamer. Performance was significantly poorer when evaluated in noise compared to performance in quiet when the TV Streamer was not used. Use of the Cochlear Wireless TV Streamer designed to stream audio from a television directly to a CI sound processor provides better speech recognition in quiet and in noise when compared to performance obtained with use of the CI sound processor alone. American Academy of Audiology.

Talker variability in audio-visual speech perception

PubMed Central

Heald, Shannon L. M.; Nusbaum, Howard C.

2014-01-01

A change in talker is a change in the context for the phonetic interpretation of acoustic patterns of speech. Different talkers have different mappings between acoustic patterns and phonetic categories and listeners need to adapt to these differences. Despite this complexity, listeners are adept at comprehending speech in multiple-talker contexts, albeit at a slight but measurable performance cost (e.g., slower recognition). So far, this talker variability cost has been demonstrated only in audio-only speech. Other research in single-talker contexts have shown, however, that when listeners are able to see a talker’s face, speech recognition is improved under adverse listening (e.g., noise or distortion) conditions that can increase uncertainty in the mapping between acoustic patterns and phonetic categories. Does seeing a talker’s face reduce the cost of word recognition in multiple-talker contexts? We used a speeded word-monitoring task in which listeners make quick judgments about target word recognition in single- and multiple-talker contexts. Results show faster recognition performance in single-talker conditions compared to multiple-talker conditions for both audio-only and audio-visual speech. However, recognition time in a multiple-talker context was slower in the audio-visual condition compared to audio-only condition. These results suggest that seeing a talker’s face during speech perception may slow recognition by increasing the importance of talker identification, signaling to the listener a change in talker has occurred. PMID:25076919

Talker variability in audio-visual speech perception.

PubMed

Heald, Shannon L M; Nusbaum, Howard C

2014-01-01

A change in talker is a change in the context for the phonetic interpretation of acoustic patterns of speech. Different talkers have different mappings between acoustic patterns and phonetic categories and listeners need to adapt to these differences. Despite this complexity, listeners are adept at comprehending speech in multiple-talker contexts, albeit at a slight but measurable performance cost (e.g., slower recognition). So far, this talker variability cost has been demonstrated only in audio-only speech. Other research in single-talker contexts have shown, however, that when listeners are able to see a talker's face, speech recognition is improved under adverse listening (e.g., noise or distortion) conditions that can increase uncertainty in the mapping between acoustic patterns and phonetic categories. Does seeing a talker's face reduce the cost of word recognition in multiple-talker contexts? We used a speeded word-monitoring task in which listeners make quick judgments about target word recognition in single- and multiple-talker contexts. Results show faster recognition performance in single-talker conditions compared to multiple-talker conditions for both audio-only and audio-visual speech. However, recognition time in a multiple-talker context was slower in the audio-visual condition compared to audio-only condition. These results suggest that seeing a talker's face during speech perception may slow recognition by increasing the importance of talker identification, signaling to the listener a change in talker has occurred.

The NTID speech recognition test: NSRT(®).

PubMed

Bochner, Joseph H; Garrison, Wayne M; Doherty, Karen A

2015-07-01

The purpose of this study was to collect and analyse data necessary for expansion of the NSRT item pool and to evaluate the NSRT adaptive testing software. Participants were administered pure-tone and speech recognition tests including W-22 and QuickSIN, as well as a set of 323 new NSRT items and NSRT adaptive tests in quiet and background noise. Performance on the adaptive tests was compared to pure-tone thresholds and performance on other speech recognition measures. The 323 new items were subjected to Rasch scaling analysis. Seventy adults with mild to moderately severe hearing loss participated in this study. Their mean age was 62.4 years (sd = 20.8). The 323 new NSRT items fit very well with the original item bank, enabling the item pool to be more than doubled in size. Data indicate high reliability coefficients for the NSRT and moderate correlations with pure-tone thresholds (PTA and HFPTA) and other speech recognition measures (W-22, QuickSIN, and SRT). The adaptive NSRT is an efficient and effective measure of speech recognition, providing valid and reliable information concerning respondents' speech perception abilities.

Does quality of life depend on speech recognition performance for adult cochlear implant users?

PubMed

Capretta, Natalie R; Moberly, Aaron C

2016-03-01

Current postoperative clinical outcome measures for adults receiving cochlear implants (CIs) consist of testing speech recognition, primarily under quiet conditions. However, it is strongly suspected that results on these measures may not adequately reflect patients' quality of life (QOL) using their implants. This study aimed to evaluate whether QOL for CI users depends on speech recognition performance. Twenty-three postlingually deafened adults with CIs were assessed. Participants were tested for speech recognition (Central Institute for the Deaf word and AzBio sentence recognition in quiet) and completed three QOL measures-the Nijmegen Cochlear Implant Questionnaire; either the Hearing Handicap Inventory for Adults or the Hearing Handicap Inventory for the Elderly; and the Speech, Spatial and Qualities of Hearing Scale questionnaires-to assess a variety of QOL factors. Correlations were sought between speech recognition and QOL scores. Demographics, audiologic history, language, and cognitive skills were also examined as potential predictors of QOL. Only a few QOL scores significantly correlated with postoperative sentence or word recognition in quiet, and correlations were primarily isolated to speech-related subscales on QOL measures. Poorer pre- and postoperative unaided hearing predicted better QOL. Socioeconomic status, duration of deafness, age at implantation, duration of CI use, reading ability, vocabulary size, and cognitive status did not consistently predict QOL scores. For adult, postlingually deafened CI users, clinical speech recognition measures in quiet do not correlate broadly with QOL. Results suggest the need for additional outcome measures of the benefits and limitations of cochlear implantation. 4. Laryngoscope, 126:699-706, 2016. © 2015 The American Laryngological, Rhinological and Otological Society, Inc.

Effect of speech-intrinsic variations on human and automatic recognition of spoken phonemes.

PubMed

Meyer, Bernd T; Brand, Thomas; Kollmeier, Birger

2011-01-01

The aim of this study is to quantify the gap between the recognition performance of human listeners and an automatic speech recognition (ASR) system with special focus on intrinsic variations of speech, such as speaking rate and effort, altered pitch, and the presence of dialect and accent. Second, it is investigated if the most common ASR features contain all information required to recognize speech in noisy environments by using resynthesized ASR features in listening experiments. For the phoneme recognition task, the ASR system achieved the human performance level only when the signal-to-noise ratio (SNR) was increased by 15 dB, which is an estimate for the human-machine gap in terms of the SNR. The major part of this gap is attributed to the feature extraction stage, since human listeners achieve comparable recognition scores when the SNR difference between unaltered and resynthesized utterances is 10 dB. Intrinsic variabilities result in strong increases of error rates, both in human speech recognition (HSR) and ASR (with a relative increase of up to 120%). An analysis of phoneme duration and recognition rates indicates that human listeners are better able to identify temporal cues than the machine at low SNRs, which suggests incorporating information about the temporal dynamics of speech into ASR systems.

Is Listening in Noise Worth It? The Neurobiology of Speech Recognition in Challenging Listening Conditions.

PubMed

Eckert, Mark A; Teubner-Rhodes, Susan; Vaden, Kenneth I

2016-01-01

This review examines findings from functional neuroimaging studies of speech recognition in noise to provide a neural systems level explanation for the effort and fatigue that can be experienced during speech recognition in challenging listening conditions. Neuroimaging studies of speech recognition consistently demonstrate that challenging listening conditions engage neural systems that are used to monitor and optimize performance across a wide range of tasks. These systems appear to improve speech recognition in younger and older adults, but sustained engagement of these systems also appears to produce an experience of effort and fatigue that may affect the value of communication. When considered in the broader context of the neuroimaging and decision making literature, the speech recognition findings from functional imaging studies indicate that the expected value, or expected level of speech recognition given the difficulty of listening conditions, should be considered when measuring effort and fatigue. The authors propose that the behavioral economics or neuroeconomics of listening can provide a conceptual and experimental framework for understanding effort and fatigue that may have clinical significance.

Is Listening in Noise Worth It? The Neurobiology of Speech Recognition in Challenging Listening Conditions

PubMed Central

Eckert, Mark A.; Teubner-Rhodes, Susan; Vaden, Kenneth I.

2016-01-01

This review examines findings from functional neuroimaging studies of speech recognition in noise to provide a neural systems level explanation for the effort and fatigue that can be experienced during speech recognition in challenging listening conditions. Neuroimaging studies of speech recognition consistently demonstrate that challenging listening conditions engage neural systems that are used to monitor and optimize performance across a wide range of tasks. These systems appear to improve speech recognition in younger and older adults, but sustained engagement of these systems also appears to produce an experience of effort and fatigue that may affect the value of communication. When considered in the broader context of the neuroimaging and decision making literature, the speech recognition findings from functional imaging studies indicate that the expected value, or expected level of speech recognition given the difficulty of listening conditions, should be considered when measuring effort and fatigue. We propose that the behavioral economics and/or neuroeconomics of listening can provide a conceptual and experimental framework for understanding effort and fatigue that may have clinical significance. PMID:27355759

Recognition of Time-Compressed and Natural Speech with Selective Temporal Enhancements by Young and Elderly Listeners

ERIC Educational Resources Information Center

Gordon-Salant, Sandra; Fitzgibbons, Peter J.; Friedman, Sarah A.

2007-01-01

Purpose: The goal of this experiment was to determine whether selective slowing of speech segments improves recognition performance by young and elderly listeners. The hypotheses were (a) the benefits of time expansion occur for rapid speech but not for natural-rate speech, (b) selective time expansion of consonants produces greater score…

Schizophrenia alters intra-network functional connectivity in the caudate for detecting speech under informational speech masking conditions.

PubMed

Zheng, Yingjun; Wu, Chao; Li, Juanhua; Li, Ruikeng; Peng, Hongjun; She, Shenglin; Ning, Yuping; Li, Liang

2018-04-04

Speech recognition under noisy "cocktail-party" environments involves multiple perceptual/cognitive processes, including target detection, selective attention, irrelevant signal inhibition, sensory/working memory, and speech production. Compared to health listeners, people with schizophrenia are more vulnerable to masking stimuli and perform worse in speech recognition under speech-on-speech masking conditions. Although the schizophrenia-related speech-recognition impairment under "cocktail-party" conditions is associated with deficits of various perceptual/cognitive processes, it is crucial to know whether the brain substrates critically underlying speech detection against informational speech masking are impaired in people with schizophrenia. Using functional magnetic resonance imaging (fMRI), this study investigated differences between people with schizophrenia (n = 19, mean age = 33 ± 10 years) and their matched healthy controls (n = 15, mean age = 30 ± 9 years) in intra-network functional connectivity (FC) specifically associated with target-speech detection under speech-on-speech-masking conditions. The target-speech detection performance under the speech-on-speech-masking condition in participants with schizophrenia was significantly worse than that in matched healthy participants (healthy controls). Moreover, in healthy controls, but not participants with schizophrenia, the strength of intra-network FC within the bilateral caudate was positively correlated with the speech-detection performance under the speech-masking conditions. Compared to controls, patients showed altered spatial activity pattern and decreased intra-network FC in the caudate. In people with schizophrenia, the declined speech-detection performance under speech-on-speech masking conditions is associated with reduced intra-caudate functional connectivity, which normally contributes to detecting target speech against speech masking via its functions of suppressing masking-speech signals.

Strategies for distant speech recognitionin reverberant environments

NASA Astrophysics Data System (ADS)

Delcroix, Marc; Yoshioka, Takuya; Ogawa, Atsunori; Kubo, Yotaro; Fujimoto, Masakiyo; Ito, Nobutaka; Kinoshita, Keisuke; Espi, Miquel; Araki, Shoko; Hori, Takaaki; Nakatani, Tomohiro

2015-12-01

Reverberation and noise are known to severely affect the automatic speech recognition (ASR) performance of speech recorded by distant microphones. Therefore, we must deal with reverberation if we are to realize high-performance hands-free speech recognition. In this paper, we review a recognition system that we developed at our laboratory to deal with reverberant speech. The system consists of a speech enhancement (SE) front-end that employs long-term linear prediction-based dereverberation followed by noise reduction. We combine our SE front-end with an ASR back-end that uses neural networks for acoustic and language modeling. The proposed system achieved top scores on the ASR task of the REVERB challenge. This paper describes the different technologies used in our system and presents detailed experimental results that justify our implementation choices and may provide hints for designing distant ASR systems.

Speech Recognition and Parent Ratings From Auditory Development Questionnaires in Children Who Are Hard of Hearing.

PubMed

McCreery, Ryan W; Walker, Elizabeth A; Spratford, Meredith; Oleson, Jacob; Bentler, Ruth; Holte, Lenore; Roush, Patricia

2015-01-01

Progress has been made in recent years in the provision of amplification and early intervention for children who are hard of hearing. However, children who use hearing aids (HAs) may have inconsistent access to their auditory environment due to limitations in speech audibility through their HAs or limited HA use. The effects of variability in children's auditory experience on parent-reported auditory skills questionnaires and on speech recognition in quiet and in noise were examined for a large group of children who were followed as part of the Outcomes of Children with Hearing Loss study. Parent ratings on auditory development questionnaires and children's speech recognition were assessed for 306 children who are hard of hearing. Children ranged in age from 12 months to 9 years. Three questionnaires involving parent ratings of auditory skill development and behavior were used, including the LittlEARS Auditory Questionnaire, Parents Evaluation of Oral/Aural Performance in Children rating scale, and an adaptation of the Speech, Spatial, and Qualities of Hearing scale. Speech recognition in quiet was assessed using the Open- and Closed-Set Test, Early Speech Perception test, Lexical Neighborhood Test, and Phonetically Balanced Kindergarten word lists. Speech recognition in noise was assessed using the Computer-Assisted Speech Perception Assessment. Children who are hard of hearing were compared with peers with normal hearing matched for age, maternal educational level, and nonverbal intelligence. The effects of aided audibility, HA use, and language ability on parent responses to auditory development questionnaires and on children's speech recognition were also examined. Children who are hard of hearing had poorer performance than peers with normal hearing on parent ratings of auditory skills and had poorer speech recognition. Significant individual variability among children who are hard of hearing was observed. Children with greater aided audibility through their HAs, more hours of HA use, and better language abilities generally had higher parent ratings of auditory skills and better speech-recognition abilities in quiet and in noise than peers with less audibility, more limited HA use, or poorer language abilities. In addition to the auditory and language factors that were predictive for speech recognition in quiet, phonological working memory was also a positive predictor for word recognition abilities in noise. Children who are hard of hearing continue to experience delays in auditory skill development and speech-recognition abilities compared with peers with normal hearing. However, significant improvements in these domains have occurred in comparison to similar data reported before the adoption of universal newborn hearing screening and early intervention programs for children who are hard of hearing. Increasing the audibility of speech has a direct positive effect on auditory skill development and speech-recognition abilities and also may enhance these skills by improving language abilities in children who are hard of hearing. Greater number of hours of HA use also had a significant positive impact on parent ratings of auditory skills and children's speech recognition.

Measuring listening effort: driving simulator vs. simple dual-task paradigm

PubMed Central

Wu, Yu-Hsiang; Aksan, Nazan; Rizzo, Matthew; Stangl, Elizabeth; Zhang, Xuyang; Bentler, Ruth

2014-01-01

Objectives The dual-task paradigm has been widely used to measure listening effort. The primary objectives of the study were to (1) investigate the effect of hearing aid amplification and a hearing aid directional technology on listening effort measured by a complicated, more real world dual-task paradigm, and (2) compare the results obtained with this paradigm to a simpler laboratory-style dual-task paradigm. Design The listening effort of adults with hearing impairment was measured using two dual-task paradigms, wherein participants performed a speech recognition task simultaneously with either a driving task in a simulator or a visual reaction-time task in a sound-treated booth. The speech materials and road noises for the speech recognition task were recorded in a van traveling on the highway in three hearing aid conditions: unaided, aided with omni directional processing (OMNI), and aided with directional processing (DIR). The change in the driving task or the visual reaction-time task performance across the conditions quantified the change in listening effort. Results Compared to the driving-only condition, driving performance declined significantly with the addition of the speech recognition task. Although the speech recognition score was higher in the OMNI and DIR conditions than in the unaided condition, driving performance was similar across these three conditions, suggesting that listening effort was not affected by amplification and directional processing. Results from the simple dual-task paradigm showed a similar trend: hearing aid technologies improved speech recognition performance, but did not affect performance in the visual reaction-time task (i.e., reduce listening effort). The correlation between listening effort measured using the driving paradigm and the visual reaction-time task paradigm was significant. The finding showing that our older (56 to 85 years old) participants’ better speech recognition performance did not result in reduced listening effort was not consistent with literature that evaluated younger (approximately 20 years old), normal hearing adults. Because of this, a follow-up study was conducted. In the follow-up study, the visual reaction-time dual-task experiment using the same speech materials and road noises was repeated on younger adults with normal hearing. Contrary to findings with older participants, the results indicated that the directional technology significantly improved performance in both speech recognition and visual reaction-time tasks. Conclusions Adding a speech listening task to driving undermined driving performance. Hearing aid technologies significantly improved speech recognition while driving, but did not significantly reduce listening effort. Listening effort measured by dual-task experiments using a simulated real-world driving task and a conventional laboratory-style task was generally consistent. For a given listening environment, the benefit of hearing aid technologies on listening effort measured from younger adults with normal hearing may not be fully translated to older listeners with hearing impairment. PMID:25083599

Automatic Speech Recognition Predicts Speech Intelligibility and Comprehension for Listeners with Simulated Age-Related Hearing Loss

ERIC Educational Resources Information Center

Fontan, Lionel; Ferrané, Isabelle; Farinas, Jérôme; Pinquier, Julien; Tardieu, Julien; Magnen, Cynthia; Gaillard, Pascal; Aumont, Xavier; Füllgrabe, Christian

2017-01-01

Purpose: The purpose of this article is to assess speech processing for listeners with simulated age-related hearing loss (ARHL) and to investigate whether the observed performance can be replicated using an automatic speech recognition (ASR) system. The long-term goal of this research is to develop a system that will assist…

Perceptual learning for speech in noise after application of binary time-frequency masks

PubMed Central

Ahmadi, Mahnaz; Gross, Vauna L.; Sinex, Donal G.

2013-01-01

Ideal time-frequency (TF) masks can reject noise and improve the recognition of speech-noise mixtures. An ideal TF mask is constructed with prior knowledge of the target speech signal. The intelligibility of a processed speech-noise mixture depends upon the threshold criterion used to define the TF mask. The study reported here assessed the effect of training on the recognition of speech in noise after processing by ideal TF masks that did not restore perfect speech intelligibility. Two groups of listeners with normal hearing listened to speech-noise mixtures processed by TF masks calculated with different threshold criteria. For each group, a threshold criterion that initially produced word recognition scores between 0.56–0.69 was chosen for training. Listeners practiced with one set of TF-masked sentences until their word recognition performance approached asymptote. Perceptual learning was quantified by comparing word-recognition scores in the first and last training sessions. Word recognition scores improved with practice for all listeners with the greatest improvement observed for the same materials used in training. PMID:23464038

Ongoing slow oscillatory phase modulates speech intelligibility in cooperation with motor cortical activity.

PubMed

Onojima, Takayuki; Kitajo, Keiichi; Mizuhara, Hiroaki

2017-01-01

Neural oscillation is attracting attention as an underlying mechanism for speech recognition. Speech intelligibility is enhanced by the synchronization of speech rhythms and slow neural oscillation, which is typically observed as human scalp electroencephalography (EEG). In addition to the effect of neural oscillation, it has been proposed that speech recognition is enhanced by the identification of a speaker's motor signals, which are used for speech production. To verify the relationship between the effect of neural oscillation and motor cortical activity, we measured scalp EEG, and simultaneous EEG and functional magnetic resonance imaging (fMRI) during a speech recognition task in which participants were required to recognize spoken words embedded in noise sound. We proposed an index to quantitatively evaluate the EEG phase effect on behavioral performance. The results showed that the delta and theta EEG phase before speech inputs modulated the participant's response time when conducting speech recognition tasks. The simultaneous EEG-fMRI experiment showed that slow EEG activity was correlated with motor cortical activity. These results suggested that the effect of the slow oscillatory phase was associated with the activity of the motor cortex during speech recognition.

Speaker normalization for chinese vowel recognition in cochlear implants.

PubMed

Luo, Xin; Fu, Qian-Jie

2005-07-01

Because of the limited spectra-temporal resolution associated with cochlear implants, implant patients often have greater difficulty with multitalker speech recognition. The present study investigated whether multitalker speech recognition can be improved by applying speaker normalization techniques to cochlear implant speech processing. Multitalker Chinese vowel recognition was tested with normal-hearing Chinese-speaking subjects listening to a 4-channel cochlear implant simulation, with and without speaker normalization. For each subject, speaker normalization was referenced to the speaker that produced the best recognition performance under conditions without speaker normalization. To match the remaining speakers to this "optimal" output pattern, the overall frequency range of the analysis filter bank was adjusted for each speaker according to the ratio of the mean third formant frequency values between the specific speaker and the reference speaker. Results showed that speaker normalization provided a small but significant improvement in subjects' overall recognition performance. After speaker normalization, subjects' patterns of recognition performance across speakers changed, demonstrating the potential for speaker-dependent effects with the proposed normalization technique.

Prediction of consonant recognition in quiet for listeners with normal and impaired hearing using an auditory model.

PubMed

Jürgens, Tim; Ewert, Stephan D; Kollmeier, Birger; Brand, Thomas

2014-03-01

Consonant recognition was assessed in normal-hearing (NH) and hearing-impaired (HI) listeners in quiet as a function of speech level using a nonsense logatome test. Average recognition scores were analyzed and compared to recognition scores of a speech recognition model. In contrast to commonly used spectral speech recognition models operating on long-term spectra, a "microscopic" model operating in the time domain was used. Variations of the model (accounting for hearing impairment) and different model parameters (reflecting cochlear compression) were tested. Using these model variations this study examined whether speech recognition performance in quiet is affected by changes in cochlear compression, namely, a linearization, which is often observed in HI listeners. Consonant recognition scores for HI listeners were poorer than for NH listeners. The model accurately predicted the speech reception thresholds of the NH and most HI listeners. A partial linearization of the cochlear compression in the auditory model, while keeping audibility constant, produced higher recognition scores and improved the prediction accuracy. However, including listener-specific information about the exact form of the cochlear compression did not improve the prediction further.

Improving on hidden Markov models: An articulatorily constrained, maximum likelihood approach to speech recognition and speech coding

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogden, J.

The goal of the proposed research is to test a statistical model of speech recognition that incorporates the knowledge that speech is produced by relatively slow motions of the tongue, lips, and other speech articulators. This model is called Maximum Likelihood Continuity Mapping (Malcom). Many speech researchers believe that by using constraints imposed by articulator motions, we can improve or replace the current hidden Markov model based speech recognition algorithms. Unfortunately, previous efforts to incorporate information about articulation into speech recognition algorithms have suffered because (1) slight inaccuracies in our knowledge or the formulation of our knowledge about articulation maymore » decrease recognition performance, (2) small changes in the assumptions underlying models of speech production can lead to large changes in the speech derived from the models, and (3) collecting measurements of human articulator positions in sufficient quantity for training a speech recognition algorithm is still impractical. The most interesting (and in fact, unique) quality of Malcom is that, even though Malcom makes use of a mapping between acoustics and articulation, Malcom can be trained to recognize speech using only acoustic data. By learning the mapping between acoustics and articulation using only acoustic data, Malcom avoids the difficulties involved in collecting articulator position measurements and does not require an articulatory synthesizer model to estimate the mapping between vocal tract shapes and speech acoustics. Preliminary experiments that demonstrate that Malcom can learn the mapping between acoustics and articulation are discussed. Potential applications of Malcom aside from speech recognition are also discussed. Finally, specific deliverables resulting from the proposed research are described.« less

Speech recognition and parent-ratings from auditory development questionnaires in children who are hard of hearing

PubMed Central

McCreery, Ryan W.; Walker, Elizabeth A.; Spratford, Meredith; Oleson, Jacob; Bentler, Ruth; Holte, Lenore; Roush, Patricia

2015-01-01

Objectives Progress has been made in recent years in the provision of amplification and early intervention for children who are hard of hearing. However, children who use hearing aids (HA) may have inconsistent access to their auditory environment due to limitations in speech audibility through their HAs or limited HA use. The effects of variability in children’s auditory experience on parent-report auditory skills questionnaires and on speech recognition in quiet and in noise were examined for a large group of children who were followed as part of the Outcomes of Children with Hearing Loss study. Design Parent ratings on auditory development questionnaires and children’s speech recognition were assessed for 306 children who are hard of hearing. Children ranged in age from 12 months to 9 years of age. Three questionnaires involving parent ratings of auditory skill development and behavior were used, including the LittlEARS Auditory Questionnaire, Parents Evaluation of Oral/Aural Performance in Children Rating Scale, and an adaptation of the Speech, Spatial and Qualities of Hearing scale. Speech recognition in quiet was assessed using the Open and Closed set task, Early Speech Perception Test, Lexical Neighborhood Test, and Phonetically-balanced Kindergarten word lists. Speech recognition in noise was assessed using the Computer-Assisted Speech Perception Assessment. Children who are hard of hearing were compared to peers with normal hearing matched for age, maternal educational level and nonverbal intelligence. The effects of aided audibility, HA use and language ability on parent responses to auditory development questionnaires and on children’s speech recognition were also examined. Results Children who are hard of hearing had poorer performance than peers with normal hearing on parent ratings of auditory skills and had poorer speech recognition. Significant individual variability among children who are hard of hearing was observed. Children with greater aided audibility through their HAs, more hours of HA use and better language abilities generally had higher parent ratings of auditory skills and better speech recognition abilities in quiet and in noise than peers with less audibility, more limited HA use or poorer language abilities. In addition to the auditory and language factors that were predictive for speech recognition in quiet, phonological working memory was also a positive predictor for word recognition abilities in noise. Conclusions Children who are hard of hearing continue to experience delays in auditory skill development and speech recognition abilities compared to peers with normal hearing. However, significant improvements in these domains have occurred in comparison to similar data reported prior to the adoption of universal newborn hearing screening and early intervention programs for children who are hard of hearing. Increasing the audibility of speech has a direct positive effect on auditory skill development and speech recognition abilities, and may also enhance these skills by improving language abilities in children who are hard of hearing. Greater number of hours of HA use also had a significant positive impact on parent ratings of auditory skills and children’s speech recognition. PMID:26731160

Emotional recognition from the speech signal for a virtual education agent

NASA Astrophysics Data System (ADS)

Tickle, A.; Raghu, S.; Elshaw, M.

2013-06-01

This paper explores the extraction of features from the speech wave to perform intelligent emotion recognition. A feature extract tool (openSmile) was used to obtain a baseline set of 998 acoustic features from a set of emotional speech recordings from a microphone. The initial features were reduced to the most important ones so recognition of emotions using a supervised neural network could be performed. Given that the future use of virtual education agents lies with making the agents more interactive, developing agents with the capability to recognise and adapt to the emotional state of humans is an important step.

Specific acoustic models for spontaneous and dictated style in indonesian speech recognition

NASA Astrophysics Data System (ADS)

Vista, C. B.; Satriawan, C. H.; Lestari, D. P.; Widyantoro, D. H.

2018-03-01

The performance of an automatic speech recognition system is affected by differences in speech style between the data the model is originally trained upon and incoming speech to be recognized. In this paper, the usage of GMM-HMM acoustic models for specific speech styles is investigated. We develop two systems for the experiments; the first employs a speech style classifier to predict the speech style of incoming speech, either spontaneous or dictated, then decodes this speech using an acoustic model specifically trained for that speech style. The second system uses both acoustic models to recognise incoming speech and decides upon a final result by calculating a confidence score of decoding. Results show that training specific acoustic models for spontaneous and dictated speech styles confers a slight recognition advantage as compared to a baseline model trained on a mixture of spontaneous and dictated training data. In addition, the speech style classifier approach of the first system produced slightly more accurate results than the confidence scoring employed in the second system.

Perception of Sung Speech in Bimodal Cochlear Implant Users.

PubMed

Crew, Joseph D; Galvin, John J; Fu, Qian-Jie

2016-11-11

Combined use of a hearing aid (HA) and cochlear implant (CI) has been shown to improve CI users' speech and music performance. However, different hearing devices, test stimuli, and listening tasks may interact and obscure bimodal benefits. In this study, speech and music perception were measured in bimodal listeners for CI-only, HA-only, and CI + HA conditions, using the Sung Speech Corpus, a database of monosyllabic words produced at different fundamental frequencies. Sentence recognition was measured using sung speech in which pitch was held constant or varied across words, as well as for spoken speech. Melodic contour identification (MCI) was measured using sung speech in which the words were held constant or varied across notes. Results showed that sentence recognition was poorer with sung speech relative to spoken, with little difference between sung speech with a constant or variable pitch; mean performance was better with CI-only relative to HA-only, and best with CI + HA. MCI performance was better with constant words versus variable words; mean performance was better with HA-only than with CI-only and was best with CI + HA. Relative to CI-only, a strong bimodal benefit was observed for speech and music perception. Relative to the better ear, bimodal benefits remained strong for sentence recognition but were marginal for MCI. While variations in pitch and timbre may negatively affect CI users' speech and music perception, bimodal listening may partially compensate for these deficits. © The Author(s) 2016.

Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity

NASA Astrophysics Data System (ADS)

Moses, David A.; Mesgarani, Nima; Leonard, Matthew K.; Chang, Edward F.

2016-10-01

Objective. The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. Approach. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. Main results. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. Significance. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

Speaker-Machine Interaction in Automatic Speech Recognition. Technical Report.

ERIC Educational Resources Information Center

Makhoul, John I.

The feasibility and limitations of speaker adaptation in improving the performance of a "fixed" (speaker-independent) automatic speech recognition system were examined. A fixed vocabulary of 55 syllables is used in the recognition system which contains 11 stops and fricatives and five tense vowels. The results of an experiment on speaker…

Noise-immune multisensor transduction of speech

NASA Astrophysics Data System (ADS)

Viswanathan, Vishu R.; Henry, Claudia M.; Derr, Alan G.; Roucos, Salim; Schwartz, Richard M.

1986-08-01

Two types of configurations of multiple sensors were developed, tested and evaluated in speech recognition application for robust performance in high levels of acoustic background noise: One type combines the individual sensor signals to provide a single speech signal input, and the other provides several parallel inputs. For single-input systems, several configurations of multiple sensors were developed and tested. Results from formal speech intelligibility and quality tests in simulated fighter aircraft cockpit noise show that each of the two-sensor configurations tested outperforms the constituent individual sensors in high noise. Also presented are results comparing the performance of two-sensor configurations and individual sensors in speaker-dependent, isolated-word speech recognition tests performed using a commercial recognizer (Verbex 4000) in simulated fighter aircraft cockpit noise.

Evaluation of speech recognizers for use in advanced combat helicopter crew station research and development

NASA Technical Reports Server (NTRS)

Simpson, Carol A.

1990-01-01

The U.S. Army Crew Station Research and Development Facility uses vintage 1984 speech recognizers. An evaluation was performed of newer off-the-shelf speech recognition devices to determine whether newer technology performance and capabilities are substantially better than that of the Army's current speech recognizers. The Phonetic Discrimination (PD-100) Test was used to compare recognizer performance in two ambient noise conditions: quiet office and helicopter noise. Test tokens were spoken by males and females and in isolated-word and connected-work mode. Better overall recognition accuracy was obtained from the newer recognizers. Recognizer capabilities needed to support the development of human factors design requirements for speech command systems in advanced combat helicopters are listed.

From Birdsong to Human Speech Recognition: Bayesian Inference on a Hierarchy of Nonlinear Dynamical Systems

PubMed Central

Yildiz, Izzet B.; von Kriegstein, Katharina; Kiebel, Stefan J.

2013-01-01

Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents—an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments. PMID:24068902

From birdsong to human speech recognition: bayesian inference on a hierarchy of nonlinear dynamical systems.

PubMed

Yildiz, Izzet B; von Kriegstein, Katharina; Kiebel, Stefan J

2013-01-01

Our knowledge about the computational mechanisms underlying human learning and recognition of sound sequences, especially speech, is still very limited. One difficulty in deciphering the exact means by which humans recognize speech is that there are scarce experimental findings at a neuronal, microscopic level. Here, we show that our neuronal-computational understanding of speech learning and recognition may be vastly improved by looking at an animal model, i.e., the songbird, which faces the same challenge as humans: to learn and decode complex auditory input, in an online fashion. Motivated by striking similarities between the human and songbird neural recognition systems at the macroscopic level, we assumed that the human brain uses the same computational principles at a microscopic level and translated a birdsong model into a novel human sound learning and recognition model with an emphasis on speech. We show that the resulting Bayesian model with a hierarchy of nonlinear dynamical systems can learn speech samples such as words rapidly and recognize them robustly, even in adverse conditions. In addition, we show that recognition can be performed even when words are spoken by different speakers and with different accents-an everyday situation in which current state-of-the-art speech recognition models often fail. The model can also be used to qualitatively explain behavioral data on human speech learning and derive predictions for future experiments.

The Effect of Remote Masking on the Reception of Speech by Young School-Age Children.

PubMed

Youngdahl, Carla L; Healy, Eric W; Yoho, Sarah E; Apoux, Frédéric; Holt, Rachael Frush

2018-02-15

Psychoacoustic data indicate that infants and children are less likely than adults to focus on a spectral region containing an anticipated signal and are more susceptible to remote masking of a signal. These detection tasks suggest that infants and children, unlike adults, do not listen selectively. However, less is known about children's ability to listen selectively during speech recognition. Accordingly, the current study examines remote masking during speech recognition in children and adults. Adults and 7- and 5-year-old children performed sentence recognition in the presence of various spectrally remote maskers. Intelligibility was determined for each remote-masker condition, and performance was compared across age groups. It was found that speech recognition for 5-year-olds was reduced in the presence of spectrally remote noise, whereas the maskers had no effect on the 7-year-olds or adults. Maskers of different bandwidth and remoteness had similar effects. In accord with psychoacoustic data, young children do not appear to focus on a spectral region of interest and ignore other regions during speech recognition. This tendency may help account for their typically poorer speech perception in noise. This study also appears to capture an important developmental stage, during which a substantial refinement in spectral listening occurs.

Investigation of potential cognitive tests for use with older adults in audiology clinics.

PubMed

Vaughan, Nancy; Storzbach, Daniel; Furukawa, Izumi

2008-01-01

Cognitive declines in working memory and processing speed are hallmarks of aging. Deficits in speech understanding also are seen in aging individuals. A clinical test to determine whether the cognitive aging changes contribute to aging speech understanding difficulties would be helpful for determining rehabilitation strategies in audiology clinics. To identify a clinical neurocognitive test or battery of tests that could be used in audiology clinics to help explain deficits in speech recognition in some older listeners. A correlational study examining the association between certain cognitive test scores and speech recognition performance. Speeded (time-compressed) speech was used to increase the cognitive processing load. Two hundred twenty-five adults aged 50 through 75 years were participants in this study. Both batteries of tests were administered to all participants in two separate sessions. A selected battery of neurocognitive tests and a time-compressed speech recognition test battery using various rates of speech were administered. Principal component analysis was used to extract the important component factors from each set of tests, and regression models were constructed to examine the association between tests and to identify the neurocognitive test most strongly associated with speech recognition performance. A sequencing working memory test (Letter-Number Sequencing [LNS]) was most strongly associated with rapid speech understanding. The association between the LNS test results and the compressed sentence recognition scores (CSRS) was strong even when age and hearing loss were controlled. The LNS is a sequencing test that provides information about temporal processing at the cognitive level and may prove useful in diagnosis of speech understanding problems, and in the development of aural rehabilitation and training strategies.

Differences in Speech Recognition Between Children with Attention Deficits and Typically Developed Children Disappear When Exposed to 65 dB of Auditory Noise

PubMed Central

Söderlund, Göran B. W.; Jobs, Elisabeth Nilsson

2016-01-01

The most common neuropsychiatric condition in the in children is attention deficit hyperactivity disorder (ADHD), affecting ∼6–9% of the population. ADHD is distinguished by inattention and hyperactive, impulsive behaviors as well as poor performance in various cognitive tasks often leading to failures at school. Sensory and perceptual dysfunctions have also been noticed. Prior research has mainly focused on limitations in executive functioning where differences are often explained by deficits in pre-frontal cortex activation. Less notice has been given to sensory perception and subcortical functioning in ADHD. Recent research has shown that children with ADHD diagnosis have a deviant auditory brain stem response compared to healthy controls. The aim of the present study was to investigate if the speech recognition threshold differs between attentive and children with ADHD symptoms in two environmental sound conditions, with and without external noise. Previous research has namely shown that children with attention deficits can benefit from white noise exposure during cognitive tasks and here we investigate if noise benefit is present during an auditory perceptual task. For this purpose we used a modified Hagerman’s speech recognition test where children with and without attention deficits performed a binaural speech recognition task to assess the speech recognition threshold in no noise and noise conditions (65 dB). Results showed that the inattentive group displayed a higher speech recognition threshold than typically developed children and that the difference in speech recognition threshold disappeared when exposed to noise at supra threshold level. From this we conclude that inattention can partly be explained by sensory perceptual limitations that can possibly be ameliorated through noise exposure. PMID:26858679

Recognition of Emotions in Mexican Spanish Speech: An Approach Based on Acoustic Modelling of Emotion-Specific Vowels

PubMed Central

Caballero-Morales, Santiago-Omar

2013-01-01

An approach for the recognition of emotions in speech is presented. The target language is Mexican Spanish, and for this purpose a speech database was created. The approach consists in the phoneme acoustic modelling of emotion-specific vowels. For this, a standard phoneme-based Automatic Speech Recognition (ASR) system was built with Hidden Markov Models (HMMs), where different phoneme HMMs were built for the consonants and emotion-specific vowels associated with four emotional states (anger, happiness, neutral, sadness). Then, estimation of the emotional state from a spoken sentence is performed by counting the number of emotion-specific vowels found in the ASR's output for the sentence. With this approach, accuracy of 87–100% was achieved for the recognition of emotional state of Mexican Spanish speech. PMID:23935410

Is talking to an automated teller machine natural and fun?

PubMed

Chan, F Y; Khalid, H M

Usability and affective issues of using automatic speech recognition technology to interact with an automated teller machine (ATM) are investigated in two experiments. The first uncovered dialogue patterns of ATM users for the purpose of designing the user interface for a simulated speech ATM system. Applying the Wizard-of-Oz methodology, multiple mapping and word spotting techniques, the speech driven ATM accommodates bilingual users of Bahasa Melayu and English. The second experiment evaluates the usability of a hybrid speech ATM, comparing it with a simulated manual ATM. The aim is to investigate how natural and fun can talking to a speech ATM be for these first-time users. Subjects performed the withdrawal and balance enquiry tasks. The ANOVA was performed on the usability and affective data. The results showed significant differences between systems in the ability to complete the tasks as well as in transaction errors. Performance was measured on the time taken by subjects to complete the task and the number of speech recognition errors that occurred. On the basis of user emotions, it can be said that the hybrid speech system enabled pleasurable interaction. Despite the limitations of speech recognition technology, users are set to talk to the ATM when it becomes available for public use.

Multilingual Phoneme Models for Rapid Speech Processing System Development

DTIC Science & Technology

2006-09-01

processes are used to develop an Arabic speech recognition system starting from monolingual English models, In- ternational Phonetic Association (IPA...clusters. It was found that multilingual bootstrapping methods out- perform monolingual English bootstrapping methods on the Arabic evaluation data initially...International Phonetic Alphabet . . . . . . . . . 7 2.3.2 Multilingual vs. Monolingual Speech Recognition 7 2.3.3 Data-Driven Approaches

Effect of a Bluetooth-implemented hearing aid on speech recognition performance: subjective and objective measurement.

PubMed

Kim, Min-Beom; Chung, Won-Ho; Choi, Jeesun; Hong, Sung Hwa; Cho, Yang-Sun; Park, Gyuseok; Lee, Sangmin

2014-06-01

The object was to evaluate speech perception improvement through Bluetooth-implemented hearing aids in hearing-impaired adults. Thirty subjects with bilateral symmetric moderate sensorineural hearing loss participated in this study. A Bluetooth-implemented hearing aid was fitted unilaterally in all study subjects. Objective speech recognition score and subjective satisfaction were measured with a Bluetooth-implemented hearing aid to replace the acoustic connection from either a cellular phone or a loudspeaker system. In each system, participants were assigned to 4 conditions: wireless speech signal transmission into hearing aid (wireless mode) in quiet or noisy environment and conventional speech signal transmission using external microphone of hearing aid (conventional mode) in quiet or noisy environment. Also, participants completed questionnaires to investigate subjective satisfaction. Both cellular phone and loudspeaker system situation, participants showed improvements in sentence and word recognition scores with wireless mode compared to conventional mode in both quiet and noise conditions (P < .001). Participants also reported subjective improvements, including better sound quality, less noise interference, and better accuracy naturalness, when using the wireless mode (P < .001). Bluetooth-implemented hearing aids helped to improve subjective and objective speech recognition performances in quiet and noisy environments during the use of electronic audio devices.

Processing F0 with cochlear implants: Modulation frequency discrimination and speech intonation recognition.

PubMed

Chatterjee, Monita; Peng, Shu-Chen

2008-01-01

Fundamental frequency (F0) processing by cochlear implant (CI) listeners was measured using a psychophysical task and a speech intonation recognition task. Listeners' Weber fractions for modulation frequency discrimination were measured using an adaptive, 3-interval, forced-choice paradigm: stimuli were presented through a custom research interface. In the speech intonation recognition task, listeners were asked to indicate whether resynthesized bisyllabic words, when presented in the free field through the listeners' everyday speech processor, were question-like or statement-like. The resynthesized tokens were systematically manipulated to have different initial-F0s to represent male vs. female voices, and different F0 contours (i.e. falling, flat, and rising) Although the CI listeners showed considerable variation in performance on both tasks, significant correlations were observed between the CI listeners' sensitivity to modulation frequency in the psychophysical task and their performance in intonation recognition. Consistent with their greater reliance on temporal cues, the CI listeners' performance in the intonation recognition task was significantly poorer with the higher initial-F0 stimuli than with the lower initial-F0 stimuli. Similar results were obtained with normal hearing listeners attending to noiseband-vocoded CI simulations with reduced spectral resolution.

Processing F0 with Cochlear Implants: Modulation Frequency Discrimination and Speech Intonation Recognition

PubMed Central

Chatterjee, Monita; Peng, Shu-Chen

2008-01-01

Fundamental frequency (F0) processing by cochlear implant (CI) listeners was measured using a psychophysical task and a speech intonation recognition task. Listeners’ Weber fractions for modulation frequency discrimination were measured using an adaptive, 3-interval, forced-choice paradigm: stimuli were presented through a custom research interface. In the speech intonation recognition task, listeners were asked to indicate whether resynthesized bisyllabic words, when presented in the free field through the listeners’ everyday speech processor, were question-like or statement-like. The resynthesized tokens were systematically manipulated to have different initial F0s to represent male vs. female voices, and different F0 contours (i.e., falling, flat, and rising) Although the CI listeners showed considerable variation in performance on both tasks, significant correlations were observed between the CI listeners’ sensitivity to modulation frequency in the psychophysical task and their performance in intonation recognition. Consistent with their greater reliance on temporal cues, the CI listeners’ performance in the intonation recognition task was significantly poorer with the higher initial-F0 stimuli than with the lower initial-F0 stimuli. Similar results were obtained with normal hearing listeners attending to noiseband-vocoded CI simulations with reduced spectral resolution. PMID:18093766

Recognizing Whispered Speech Produced by an Individual with Surgically Reconstructed Larynx Using Articulatory Movement Data

PubMed Central

Cao, Beiming; Kim, Myungjong; Mau, Ted; Wang, Jun

2017-01-01

Individuals with larynx (vocal folds) impaired have problems in controlling their glottal vibration, producing whispered speech with extreme hoarseness. Standard automatic speech recognition using only acoustic cues is typically ineffective for whispered speech because the corresponding spectral characteristics are distorted. Articulatory cues such as the tongue and lip motion may help in recognizing whispered speech since articulatory motion patterns are generally not affected. In this paper, we investigated whispered speech recognition for patients with reconstructed larynx using articulatory movement data. A data set with both acoustic and articulatory motion data was collected from a patient with surgically reconstructed larynx using an electromagnetic articulograph. Two speech recognition systems, Gaussian mixture model-hidden Markov model (GMM-HMM) and deep neural network-HMM (DNN-HMM), were used in the experiments. Experimental results showed adding either tongue or lip motion data to acoustic features such as mel-frequency cepstral coefficient (MFCC) significantly reduced the phone error rates on both speech recognition systems. Adding both tongue and lip data achieved the best performance. PMID:29423453

Factors that influence the performance of experienced speech recognition users.

PubMed

Koester, Heidi Horstmann

2006-01-01

Performance on automatic speech recognition (ASR) systems for users with physical disabilities varies widely between individuals. The goal of this study was to discover some key factors that account for that variation. Using data from 23 experienced ASR users with physical disabilities, the effect of 20 different independent variables on recognition accuracy and text entry rate with ASR was measured using bivariate and multivariate analyses. The results show that use of appropriate correction strategies had the strongest influence on user performance with ASR. The amount of time the user spent on his or her computer, the user's manual typing speed, and the speed with which the ASR system recognized speech were all positively associated with better performance. The amount or perceived adequacy of ASR training did not have a significant impact on performance for this user group.

Noise-robust speech recognition through auditory feature detection and spike sequence decoding.

PubMed

Schafer, Phillip B; Jin, Dezhe Z

2014-03-01

Speech recognition in noisy conditions is a major challenge for computer systems, but the human brain performs it routinely and accurately. Automatic speech recognition (ASR) systems that are inspired by neuroscience can potentially bridge the performance gap between humans and machines. We present a system for noise-robust isolated word recognition that works by decoding sequences of spikes from a population of simulated auditory feature-detecting neurons. Each neuron is trained to respond selectively to a brief spectrotemporal pattern, or feature, drawn from the simulated auditory nerve response to speech. The neural population conveys the time-dependent structure of a sound by its sequence of spikes. We compare two methods for decoding the spike sequences--one using a hidden Markov model-based recognizer, the other using a novel template-based recognition scheme. In the latter case, words are recognized by comparing their spike sequences to template sequences obtained from clean training data, using a similarity measure based on the length of the longest common sub-sequence. Using isolated spoken digits from the AURORA-2 database, we show that our combined system outperforms a state-of-the-art robust speech recognizer at low signal-to-noise ratios. Both the spike-based encoding scheme and the template-based decoding offer gains in noise robustness over traditional speech recognition methods. Our system highlights potential advantages of spike-based acoustic coding and provides a biologically motivated framework for robust ASR development.

Speech Perception in Noise by Children With Cochlear Implants

PubMed Central

Caldwell, Amanda; Nittrouer, Susan

2013-01-01

Purpose Common wisdom suggests that listening in noise poses disproportionately greater difficulty for listeners with cochlear implants (CIs) than for peers with normal hearing (NH). The purpose of this study was to examine phonological, language, and cognitive skills that might help explain speech-in-noise abilities for children with CIs. Method Three groups of kindergartners (NH, hearing aid wearers, and CI users) were tested on speech recognition in quiet and noise and on tasks thought to underlie the abilities that fit into the domains of phonological awareness, general language, and cognitive skills. These last measures were used as predictor variables in regression analyses with speech-in-noise scores as dependent variables. Results Compared to children with NH, children with CIs did not perform as well on speech recognition in noise or on most other measures, including recognition in quiet. Two surprising results were that (a) noise effects were consistent across groups and (b) scores on other measures did not explain any group differences in speech recognition. Conclusions Limitations of implant processing take their primary toll on recognition in quiet and account for poor speech recognition and language/phonological deficits in children with CIs. Implications are that teachers/clinicians need to teach language/phonology directly and maximize signal-to-noise levels in the classroom. PMID:22744138

Simulation of talking faces in the human brain improves auditory speech recognition

PubMed Central

von Kriegstein, Katharina; Dogan, Özgür; Grüter, Martina; Giraud, Anne-Lise; Kell, Christian A.; Grüter, Thomas; Kleinschmidt, Andreas; Kiebel, Stefan J.

2008-01-01

Human face-to-face communication is essentially audiovisual. Typically, people talk to us face-to-face, providing concurrent auditory and visual input. Understanding someone is easier when there is visual input, because visual cues like mouth and tongue movements provide complementary information about speech content. Here, we hypothesized that, even in the absence of visual input, the brain optimizes both auditory-only speech and speaker recognition by harvesting speaker-specific predictions and constraints from distinct visual face-processing areas. To test this hypothesis, we performed behavioral and neuroimaging experiments in two groups: subjects with a face recognition deficit (prosopagnosia) and matched controls. The results show that observing a specific person talking for 2 min improves subsequent auditory-only speech and speaker recognition for this person. In both prosopagnosics and controls, behavioral improvement in auditory-only speech recognition was based on an area typically involved in face-movement processing. Improvement in speaker recognition was only present in controls and was based on an area involved in face-identity processing. These findings challenge current unisensory models of speech processing, because they show that, in auditory-only speech, the brain exploits previously encoded audiovisual correlations to optimize communication. We suggest that this optimization is based on speaker-specific audiovisual internal models, which are used to simulate a talking face. PMID:18436648

A voice-input voice-output communication aid for people with severe speech impairment.

PubMed

Hawley, Mark S; Cunningham, Stuart P; Green, Phil D; Enderby, Pam; Palmer, Rebecca; Sehgal, Siddharth; O'Neill, Peter

2013-01-01

A new form of augmentative and alternative communication (AAC) device for people with severe speech impairment-the voice-input voice-output communication aid (VIVOCA)-is described. The VIVOCA recognizes the disordered speech of the user and builds messages, which are converted into synthetic speech. System development was carried out employing user-centered design and development methods, which identified and refined key requirements for the device. A novel methodology for building small vocabulary, speaker-dependent automatic speech recognizers with reduced amounts of training data, was applied. Experiments showed that this method is successful in generating good recognition performance (mean accuracy 96%) on highly disordered speech, even when recognition perplexity is increased. The selected message-building technique traded off various factors including speed of message construction and range of available message outputs. The VIVOCA was evaluated in a field trial by individuals with moderate to severe dysarthria and confirmed that they can make use of the device to produce intelligible speech output from disordered speech input. The trial highlighted some issues which limit the performance and usability of the device when applied in real usage situations, with mean recognition accuracy of 67% in these circumstances. These limitations will be addressed in future work.

V2S: Voice to Sign Language Translation System for Malaysian Deaf People

NASA Astrophysics Data System (ADS)

Mean Foong, Oi; Low, Tang Jung; La, Wai Wan

The process of learning and understand the sign language may be cumbersome to some, and therefore, this paper proposes a solution to this problem by providing a voice (English Language) to sign language translation system using Speech and Image processing technique. Speech processing which includes Speech Recognition is the study of recognizing the words being spoken, regardless of whom the speaker is. This project uses template-based recognition as the main approach in which the V2S system first needs to be trained with speech pattern based on some generic spectral parameter set. These spectral parameter set will then be stored as template in a database. The system will perform the recognition process through matching the parameter set of the input speech with the stored templates to finally display the sign language in video format. Empirical results show that the system has 80.3% recognition rate.

Assessment of Spectral and Temporal Resolution in Cochlear Implant Users Using Psychoacoustic Discrimination and Speech Cue Categorization.

PubMed

Winn, Matthew B; Won, Jong Ho; Moon, Il Joon

This study was conducted to measure auditory perception by cochlear implant users in the spectral and temporal domains, using tests of either categorization (using speech-based cues) or discrimination (using conventional psychoacoustic tests). The authors hypothesized that traditional nonlinguistic tests assessing spectral and temporal auditory resolution would correspond to speech-based measures assessing specific aspects of phonetic categorization assumed to depend on spectral and temporal auditory resolution. The authors further hypothesized that speech-based categorization performance would ultimately be a superior predictor of speech recognition performance, because of the fundamental nature of speech recognition as categorization. Nineteen cochlear implant listeners and 10 listeners with normal hearing participated in a suite of tasks that included spectral ripple discrimination, temporal modulation detection, and syllable categorization, which was split into a spectral cue-based task (targeting the /ba/-/da/ contrast) and a timing cue-based task (targeting the /b/-/p/ and /d/-/t/ contrasts). Speech sounds were manipulated to contain specific spectral or temporal modulations (formant transitions or voice onset time, respectively) that could be categorized. Categorization responses were quantified using logistic regression to assess perceptual sensitivity to acoustic phonetic cues. Word recognition testing was also conducted for cochlear implant listeners. Cochlear implant users were generally less successful at utilizing both spectral and temporal cues for categorization compared with listeners with normal hearing. For the cochlear implant listener group, spectral ripple discrimination was significantly correlated with the categorization of formant transitions; both were correlated with better word recognition. Temporal modulation detection using 100- and 10-Hz-modulated noise was not correlated either with the cochlear implant subjects' categorization of voice onset time or with word recognition. Word recognition was correlated more closely with categorization of the controlled speech cues than with performance on the psychophysical discrimination tasks. When evaluating people with cochlear implants, controlled speech-based stimuli are feasible to use in tests of auditory cue categorization, to complement traditional measures of auditory discrimination. Stimuli based on specific speech cues correspond to counterpart nonlinguistic measures of discrimination, but potentially show better correspondence with speech perception more generally. The ubiquity of the spectral (formant transition) and temporal (voice onset time) stimulus dimensions across languages highlights the potential to use this testing approach even in cases where English is not the native language.

Assessment of spectral and temporal resolution in cochlear implant users using psychoacoustic discrimination and speech cue categorization

PubMed Central

Winn, Matthew B.; Won, Jong Ho; Moon, Il Joon

2016-01-01

Objectives This study was conducted to measure auditory perception by cochlear implant users in the spectral and temporal domains, using tests of either categorization (using speech-based cues) or discrimination (using conventional psychoacoustic tests). We hypothesized that traditional nonlinguistic tests assessing spectral and temporal auditory resolution would correspond to speech-based measures assessing specific aspects of phonetic categorization assumed to depend on spectral and temporal auditory resolution. We further hypothesized that speech-based categorization performance would ultimately be a superior predictor of speech recognition performance, because of the fundamental nature of speech recognition as categorization. Design Nineteen CI listeners and 10 listeners with normal hearing (NH) participated in a suite of tasks that included spectral ripple discrimination (SRD), temporal modulation detection (TMD), and syllable categorization, which was split into a spectral-cue-based task (targeting the /ba/-/da/ contrast) and a timing-cue-based task (targeting the /b/-/p/ and /d/-/t/ contrasts). Speech sounds were manipulated in order to contain specific spectral or temporal modulations (formant transitions or voice onset time, respectively) that could be categorized. Categorization responses were quantified using logistic regression in order to assess perceptual sensitivity to acoustic phonetic cues. Word recognition testing was also conducted for CI listeners. Results CI users were generally less successful at utilizing both spectral and temporal cues for categorization compared to listeners with normal hearing. For the CI listener group, SRD was significantly correlated with the categorization of formant transitions; both were correlated with better word recognition. TMD using 100 Hz and 10 Hz modulated noise was not correlated with the CI subjects’ categorization of VOT, nor with word recognition. Word recognition was correlated more closely with categorization of the controlled speech cues than with performance on the psychophysical discrimination tasks. Conclusions When evaluating people with cochlear implants, controlled speech-based stimuli are feasible to use in tests of auditory cue categorization, to complement traditional measures of auditory discrimination. Stimuli based on specific speech cues correspond to counterpart non-linguistic measures of discrimination, but potentially show better correspondence with speech perception more generally. The ubiquity of the spectral (formant transition) and temporal (VOT) stimulus dimensions across languages highlights the potential to use this testing approach even in cases where English is not the native language. PMID:27438871

Lexical-Access Ability and Cognitive Predictors of Speech Recognition in Noise in Adult Cochlear Implant Users

PubMed Central

Smits, Cas; Merkus, Paul; Festen, Joost M.; Goverts, S. Theo

2017-01-01

Not all of the variance in speech-recognition performance of cochlear implant (CI) users can be explained by biographic and auditory factors. In normal-hearing listeners, linguistic and cognitive factors determine most of speech-in-noise performance. The current study explored specifically the influence of visually measured lexical-access ability compared with other cognitive factors on speech recognition of 24 postlingually deafened CI users. Speech-recognition performance was measured with monosyllables in quiet (consonant-vowel-consonant [CVC]), sentences-in-noise (SIN), and digit-triplets in noise (DIN). In addition to a composite variable of lexical-access ability (LA), measured with a lexical-decision test (LDT) and word-naming task, vocabulary size, working-memory capacity (Reading Span test [RSpan]), and a visual analogue of the SIN test (text reception threshold test) were measured. The DIN test was used to correct for auditory factors in SIN thresholds by taking the difference between SIN and DIN: SRTdiff. Correlation analyses revealed that duration of hearing loss (dHL) was related to SIN thresholds. Better working-memory capacity was related to SIN and SRTdiff scores. LDT reaction time was positively correlated with SRTdiff scores. No significant relationships were found for CVC or DIN scores with the predictor variables. Regression analyses showed that together with dHL, RSpan explained 55% of the variance in SIN thresholds. When controlling for auditory performance, LA, LDT, and RSpan separately explained, together with dHL, respectively 37%, 36%, and 46% of the variance in SRTdiff outcome. The results suggest that poor verbal working-memory capacity and to a lesser extent poor lexical-access ability limit speech-recognition ability in listeners with a CI. PMID:29205095

Evaluating deep learning architectures for Speech Emotion Recognition.

PubMed

Fayek, Haytham M; Lech, Margaret; Cavedon, Lawrence

2017-08-01

Speech Emotion Recognition (SER) can be regarded as a static or dynamic classification problem, which makes SER an excellent test bed for investigating and comparing various deep learning architectures. We describe a frame-based formulation to SER that relies on minimal speech processing and end-to-end deep learning to model intra-utterance dynamics. We use the proposed SER system to empirically explore feed-forward and recurrent neural network architectures and their variants. Experiments conducted illuminate the advantages and limitations of these architectures in paralinguistic speech recognition and emotion recognition in particular. As a result of our exploration, we report state-of-the-art results on the IEMOCAP database for speaker-independent SER and present quantitative and qualitative assessments of the models' performances. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hierarchical singleton-type recurrent neural fuzzy networks for noisy speech recognition.

PubMed

Juang, Chia-Feng; Chiou, Chyi-Tian; Lai, Chun-Lung

2007-05-01

This paper proposes noisy speech recognition using hierarchical singleton-type recurrent neural fuzzy networks (HSRNFNs). The proposed HSRNFN is a hierarchical connection of two singleton-type recurrent neural fuzzy networks (SRNFNs), where one is used for noise filtering and the other for recognition. The SRNFN is constructed by recurrent fuzzy if-then rules with fuzzy singletons in the consequences, and their recurrent properties make them suitable for processing speech patterns with temporal characteristics. In n words recognition, n SRNFNs are created for modeling n words, where each SRNFN receives the current frame feature and predicts the next one of its modeling word. The prediction error of each SRNFN is used as recognition criterion. In filtering, one SRNFN is created, and each SRNFN recognizer is connected to the same SRNFN filter, which filters noisy speech patterns in the feature domain before feeding them to the SRNFN recognizer. Experiments with Mandarin word recognition under different types of noise are performed. Other recognizers, including multilayer perceptron (MLP), time-delay neural networks (TDNNs), and hidden Markov models (HMMs), are also tested and compared. These experiments and comparisons demonstrate good results with HSRNFN for noisy speech recognition tasks.

Speech recognition in one- and two-talker maskers in school-age children and adults: Development of perceptual masking and glimpsing

PubMed Central

Buss, Emily; Leibold, Lori J.; Porter, Heather L.; Grose, John H.

2017-01-01

Children perform more poorly than adults on a wide range of masked speech perception paradigms, but this effect is particularly pronounced when the masker itself is also composed of speech. The present study evaluated two factors that might contribute to this effect: the ability to perceptually isolate the target from masker speech, and the ability to recognize target speech based on sparse cues (glimpsing). Speech reception thresholds (SRTs) were estimated for closed-set, disyllabic word recognition in children (5–16 years) and adults in a one- or two-talker masker. Speech maskers were 60 dB sound pressure level (SPL), and they were either presented alone or in combination with a 50-dB-SPL speech-shaped noise masker. There was an age effect overall, but performance was adult-like at a younger age for the one-talker than the two-talker masker. Noise tended to elevate SRTs, particularly for older children and adults, and when summed with the one-talker masker. Removing time-frequency epochs associated with a poor target-to-masker ratio markedly improved SRTs, with larger effects for younger listeners; the age effect was not eliminated, however. Results were interpreted as indicating that development of speech-in-speech recognition is likely impacted by development of both perceptual masking and the ability recognize speech based on sparse cues. PMID:28464682

Working memory capacity may influence perceived effort during aided speech recognition in noise.

PubMed

Rudner, Mary; Lunner, Thomas; Behrens, Thomas; Thorén, Elisabet Sundewall; Rönnberg, Jerker

2012-09-01

Recently there has been interest in using subjective ratings as a measure of perceived effort during speech recognition in noise. Perceived effort may be an indicator of cognitive load. Thus, subjective effort ratings during speech recognition in noise may covary both with signal-to-noise ratio (SNR) and individual cognitive capacity. The present study investigated the relation between subjective ratings of the effort involved in listening to speech in noise, speech recognition performance, and individual working memory (WM) capacity in hearing impaired hearing aid users. In two experiments, participants with hearing loss rated perceived effort during aided speech perception in noise. Noise type and SNR were manipulated in both experiments, and in the second experiment hearing aid compression release settings were also manipulated. Speech recognition performance was measured along with WM capacity. There were 46 participants in all with bilateral mild to moderate sloping hearing loss. In Experiment 1 there were 16 native Danish speakers (eight women and eight men) with a mean age of 63.5 yr (SD = 12.1) and average pure tone (PT) threshold of 47. 6 dB (SD = 9.8). In Experiment 2 there were 30 native Swedish speakers (19 women and 11 men) with a mean age of 70 yr (SD = 7.8) and average PT threshold of 45.8 dB (SD = 6.6). A visual analog scale (VAS) was used for effort rating in both experiments. In Experiment 1, effort was rated at individually adapted SNRs while in Experiment 2 it was rated at fixed SNRs. Speech recognition in noise performance was measured using adaptive procedures in both experiments with Dantale II sentences in Experiment 1 and Hagerman sentences in Experiment 2. WM capacity was measured using a letter-monitoring task in Experiment 1 and the reading span task in Experiment 2. In both experiments, there was a strong and significant relation between rated effort and SNR that was independent of individual WM capacity, whereas the relation between rated effort and noise type seemed to be influenced by individual WM capacity. Experiment 2 showed that hearing aid compression setting influenced rated effort. Subjective ratings of the effort involved in speech recognition in noise reflect SNRs, and individual cognitive capacity seems to influence relative rating of noise type. American Academy of Audiology.

Automatic speech recognition (ASR) based approach for speech therapy of aphasic patients: A review

NASA Astrophysics Data System (ADS)

Jamal, Norezmi; Shanta, Shahnoor; Mahmud, Farhanahani; Sha'abani, MNAH

2017-09-01

This paper reviews the state-of-the-art an automatic speech recognition (ASR) based approach for speech therapy of aphasic patients. Aphasia is a condition in which the affected person suffers from speech and language disorder resulting from a stroke or brain injury. Since there is a growing body of evidence indicating the possibility of improving the symptoms at an early stage, ASR based solutions are increasingly being researched for speech and language therapy. ASR is a technology that transfers human speech into transcript text by matching with the system's library. This is particularly useful in speech rehabilitation therapies as they provide accurate, real-time evaluation for speech input from an individual with speech disorder. ASR based approaches for speech therapy recognize the speech input from the aphasic patient and provide real-time feedback response to their mistakes. However, the accuracy of ASR is dependent on many factors such as, phoneme recognition, speech continuity, speaker and environmental differences as well as our depth of knowledge on human language understanding. Hence, the review examines recent development of ASR technologies and its performance for individuals with speech and language disorders.

A longitudinal study of the bilateral benefit in children with bilateral cochlear implants.

PubMed

Asp, Filip; Mäki-Torkko, Elina; Karltorp, Eva; Harder, Henrik; Hergils, Leif; Eskilsson, Gunnar; Stenfelt, Stefan

2015-02-01

To study the development of the bilateral benefit in children using bilateral cochlear implants by measurements of speech recognition and sound localization. Bilateral and unilateral speech recognition in quiet, in multi-source noise, and horizontal sound localization was measured at three occasions during a two-year period, without controlling for age or implant experience. Longitudinal and cross-sectional analyses were performed. Results were compared to cross-sectional data from children with normal hearing. Seventy-eight children aged 5.1-11.9 years, with a mean bilateral cochlear implant experience of 3.3 years and a mean age of 7.8 years, at inclusion in the study. Thirty children with normal hearing aged 4.8-9.0 years provided normative data. For children with cochlear implants, bilateral and unilateral speech recognition in quiet was comparable whereas a bilateral benefit for speech recognition in noise and sound localization was found at all three test occasions. Absolute performance was lower than in children with normal hearing. Early bilateral implantation facilitated sound localization. A bilateral benefit for speech recognition in noise and sound localization continues to exist over time for children with bilateral cochlear implants, but no relative improvement is found after three years of bilateral cochlear implant experience.

Music Training Can Improve Music and Speech Perception in Pediatric Mandarin-Speaking Cochlear Implant Users.

PubMed

Cheng, Xiaoting; Liu, Yangwenyi; Shu, Yilai; Tao, Duo-Duo; Wang, Bing; Yuan, Yasheng; Galvin, John J; Fu, Qian-Jie; Chen, Bing

2018-01-01

Due to limited spectral resolution, cochlear implants (CIs) do not convey pitch information very well. Pitch cues are important for perception of music and tonal language; it is possible that music training may improve performance in both listening tasks. In this study, we investigated music training outcomes in terms of perception of music, lexical tones, and sentences in 22 young (4.8 to 9.3 years old), prelingually deaf Mandarin-speaking CI users. Music perception was measured using a melodic contour identification (MCI) task. Speech perception was measured for lexical tones and sentences presented in quiet. Subjects received 8 weeks of MCI training using pitch ranges not used for testing. Music and speech perception were measured at 2, 4, and 8 weeks after training was begun; follow-up measures were made 4 weeks after training was stopped. Mean baseline performance was 33.2%, 76.9%, and 45.8% correct for MCI, lexical tone recognition, and sentence recognition, respectively. After 8 weeks of MCI training, mean performance significantly improved by 22.9, 14.4, and 14.5 percentage points for MCI, lexical tone recognition, and sentence recognition, respectively ( p < .05 in all cases). Four weeks after training was stopped, there was no significant change in posttraining music and speech performance. The results suggest that music training can significantly improve pediatric Mandarin-speaking CI users' music and speech perception.

Effects of noise on speech recognition: Challenges for communication by service members.

PubMed

Le Prell, Colleen G; Clavier, Odile H

2017-06-01

Speech communication often takes place in noisy environments; this is an urgent issue for military personnel who must communicate in high-noise environments. The effects of noise on speech recognition vary significantly according to the sources of noise, the number and types of talkers, and the listener's hearing ability. In this review, speech communication is first described as it relates to current standards of hearing assessment for military and civilian populations. The next section categorizes types of noise (also called maskers) according to their temporal characteristics (steady or fluctuating) and perceptive effects (energetic or informational masking). Next, speech recognition difficulties experienced by listeners with hearing loss and by older listeners are summarized, and questions on the possible causes of speech-in-noise difficulty are discussed, including recent suggestions of "hidden hearing loss". The final section describes tests used by military and civilian researchers, audiologists, and hearing technicians to assess performance of an individual in recognizing speech in background noise, as well as metrics that predict performance based on a listener and background noise profile. This article provides readers with an overview of the challenges associated with speech communication in noisy backgrounds, as well as its assessment and potential impact on functional performance, and provides guidance for important new research directions relevant not only to military personnel, but also to employees who work in high noise environments. Copyright © 2016 Elsevier B.V. All rights reserved.

Speech Recognition Using Multiple Features and Multiple Recognizers

DTIC Science & Technology

1991-12-03

6 2.1 Introduction ............................................... 6 2.2 Human Speech Communication Process...119 How to Setup ASRT.......................................... 119 How to Use Interactive Menus .................................. 120...recognize a word from an acoustic signal. The human ear and brain perform this type of recognition with incredible speed and precision. Even though

Speech recognition for bilaterally asymmetric and symmetric hearing aid microphone modes in simulated classroom environments.

PubMed

Ricketts, Todd A; Picou, Erin M

2013-09-01

This study aimed to evaluate the potential utility of asymmetrical and symmetrical directional hearing aid fittings for school-age children in simulated classroom environments. This study also aimed to evaluate speech recognition performance of children with normal hearing in the same listening environments. Two groups of school-age children 11 to 17 years of age participated in this study. Twenty participants had normal hearing, and 29 participants had sensorineural hearing loss. Participants with hearing loss were fitted with behind-the-ear hearing aids with clinically appropriate venting and were tested in 3 hearing aid configurations: bilateral omnidirectional, bilateral directional, and asymmetrical directional microphones. Speech recognition testing was completed in each microphone configuration in 3 environments: Talker-Front, Talker-Back, and Question-Answer situations. During testing, the location of the speech signal changed, but participants were always seated in a noisy, moderately reverberant classroom-like room. For all conditions, results revealed expected effects of directional microphones on speech recognition performance. When the signal of interest was in front of the listener, bilateral directional microphone was best, and when the signal of interest was behind the listener, bilateral omnidirectional microphone was best. Performance with asymmetric directional microphones was between the 2 symmetrical conditions. The magnitudes of directional benefits and decrements were not significantly correlated. In comparison with their peers with normal hearing, children with hearing loss performed similarly to their peers with normal hearing when fitted with directional microphones and the speech was from the front. In contrast, children with normal hearing still outperformed children with hearing loss if the speech originated from behind, even when the children were fitted with the optimal hearing aid microphone mode for the situation. Bilateral directional microphones can be effective in improving speech recognition performance for children in the classroom, as long as child is facing the talker of interest. Bilateral directional microphones, however, can impair performance if the signal originates from behind a listener. However, these data suggest that the magnitude of decrement is not predictable from an individual's benefit. The results re-emphasize the importance of appropriate switching between microphone modes so children can take full advantage of directional benefits without being hurt by directional decrements. An asymmetric fitting limits decrements, but does not lead to maximum speech recognition scores when compared with the optimal symmetrical fitting. Therefore, the asymmetric mode may not be the best option as a default fitting for children in a classroom environment. While directional microphones improve performance for children with hearing loss, their performance in most conditions continues to be impaired relative to their normal-hearing peers, particularly when the signals of interest originate from behind or from an unpredictable location.

The effect of hearing aid technologies on listening in an automobile.

PubMed

Wu, Yu-Hsiang; Stangl, Elizabeth; Bentler, Ruth A; Stanziola, Rachel W

2013-06-01

Communication while traveling in an automobile often is very difficult for hearing aid users. This is because the automobile/road noise level is usually high, and listeners/drivers often do not have access to visual cues. Since the talker of interest usually is not located in front of the listener/driver, conventional directional processing that places the directivity beam toward the listener's front may not be helpful and, in fact, could have a negative impact on speech recognition (when compared to omnidirectional processing). Recently, technologies have become available in commercial hearing aids that are designed to improve speech recognition and/or listening effort in noisy conditions where talkers are located behind or beside the listener. These technologies include (1) a directional microphone system that uses a backward-facing directivity pattern (Back-DIR processing), (2) a technology that transmits audio signals from the ear with the better signal-to-noise ratio (SNR) to the ear with the poorer SNR (Side-Transmission processing), and (3) a signal processing scheme that suppresses the noise at the ear with the poorer SNR (Side-Suppression processing). The purpose of the current study was to determine the effect of (1) conventional directional microphones and (2) newer signal processing schemes (Back-DIR, Side-Transmission, and Side-Suppression) on listener's speech recognition performance and preference for communication in a traveling automobile. A single-blinded, repeated-measures design was used. Twenty-five adults with bilateral symmetrical sensorineural hearing loss aged 44 through 84 yr participated in the study. The automobile/road noise and sentences of the Connected Speech Test (CST) were recorded through hearing aids in a standard van moving at a speed of 70 mph on a paved highway. The hearing aids were programmed to omnidirectional microphone, conventional adaptive directional microphone, and the three newer schemes. CST sentences were presented from the side and back of the hearing aids, which were placed on the ears of a manikin. The recorded stimuli were presented to listeners via earphones in a sound-treated booth to assess speech recognition performance and preference with each programmed condition. Compared to omnidirectional microphones, conventional adaptive directional processing had a detrimental effect on speech recognition when speech was presented from the back or side of the listener. Back-DIR and Side-Transmission processing improved speech recognition performance (relative to both omnidirectional and adaptive directional processing) when speech was from the back and side, respectively. The performance with Side-Suppression processing was better than with adaptive directional processing when speech was from the side. The participants' preferences for a given processing scheme were generally consistent with speech recognition results. The finding that performance with adaptive directional processing was poorer than with omnidirectional microphones demonstrates the importance of selecting the correct microphone technology for different listening situations. The results also suggest the feasibility of using hearing aid technologies to provide a better listening experience for hearing aid users in automobiles. American Academy of Audiology.

A novel speech processing algorithm based on harmonicity cues in cochlear implant

NASA Astrophysics Data System (ADS)

Wang, Jian; Chen, Yousheng; Zhang, Zongping; Chen, Yan; Zhang, Weifeng

2017-08-01

This paper proposed a novel speech processing algorithm in cochlear implant, which used harmonicity cues to enhance tonal information in Mandarin Chinese speech recognition. The input speech was filtered by a 4-channel band-pass filter bank. The frequency ranges for the four bands were: 300-621, 621-1285, 1285-2657, and 2657-5499 Hz. In each pass band, temporal envelope and periodicity cues (TEPCs) below 400 Hz were extracted by full wave rectification and low-pass filtering. The TEPCs were modulated by a sinusoidal carrier, the frequency of which was fundamental frequency (F0) and its harmonics most close to the center frequency of each band. Signals from each band were combined together to obtain an output speech. Mandarin tone, word, and sentence recognition in quiet listening conditions were tested for the extensively used continuous interleaved sampling (CIS) strategy and the novel F0-harmonic algorithm. Results found that the F0-harmonic algorithm performed consistently better than CIS strategy in Mandarin tone, word, and sentence recognition. In addition, sentence recognition rate was higher than word recognition rate, as a result of contextual information in the sentence. Moreover, tone 3 and 4 performed better than tone 1 and tone 2, due to the easily identified features of the former. In conclusion, the F0-harmonic algorithm could enhance tonal information in cochlear implant speech processing due to the use of harmonicity cues, thereby improving Mandarin tone, word, and sentence recognition. Further study will focus on the test of the F0-harmonic algorithm in noisy listening conditions.

Electromagnetic versus electrical coupling of personal frequency modulation (FM) receivers to cochlear implant sound processors.

PubMed

Schafer, Erin C; Romine, Denise; Musgrave, Elizabeth; Momin, Sadaf; Huynh, Christy

2013-01-01

Previous research has suggested that electrically coupled frequency modulation (FM) systems substantially improved speech-recognition performance in noise in individuals with cochlear implants (CIs). However, there is limited evidence to support the use of electromagnetically coupled (neck loop) FM receivers with contemporary CI sound processors containing telecoils. The primary goal of this study was to compare speech-recognition performance in noise and subjective ratings of adolescents and adults using one of three contemporary CI sound processors coupled to electromagnetically and electrically coupled FM receivers from Oticon. A repeated-measures design was used to compare speech-recognition performance in noise and subjective ratings without and with the FM systems across three test sessions (Experiment 1) and to compare performance at different FM-gain settings (Experiment 2). Descriptive statistics were used in Experiment 3 to describe output differences measured through a CI sound processor. Experiment 1 included nine adolescents or adults with unilateral or bilateral Advanced Bionics Harmony (n = 3), Cochlear Nucleus 5 (n = 3), and MED-EL OPUS 2 (n = 3) CI sound processors. In Experiment 2, seven of the original nine participants were tested. In Experiment 3, electroacoustic output was measured from a Nucleus 5 sound processor when coupled to the electromagnetically coupled Oticon Arc neck loop and electrically coupled Oticon R2. In Experiment 1, participants completed a field trial with each FM receiver and three test sessions that included speech-recognition performance in noise and a subjective rating scale. In Experiment 2, participants were tested in three receiver-gain conditions. Results in both experiments were analyzed using repeated-measures analysis of variance. Experiment 3 involved electroacoustic-test measures to determine the monitor-earphone output of the CI alone and CI coupled to the two FM receivers. The results in Experiment 1 suggested that both FM receivers provided significantly better speech-recognition performance in noise than the CI alone; however, the electromagnetically coupled receiver provided significantly better speech-recognition performance in noise and better ratings in some situations than the electrically coupled receiver when set to the same gain. In Experiment 2, the primary analysis suggested significantly better speech-recognition performance in noise for the neck-loop versus electrically coupled receiver, but a second analysis, using the best performance across gain settings for each device, revealed no significant differences between the two FM receivers. Experiment 3 revealed monitor-earphone output differences in the Nucleus 5 sound processor for the two FM receivers when set to the +8 setting used in Experiment 1 but equal output when the electrically coupled device was set to a +16 gain setting and the electromagnetically coupled device was set to the +8 gain setting. Individuals with contemporary sound processors may show more favorable speech-recognition performance in noise electromagnetically coupled FM systems (i.e., Oticon Arc), which is most likely related to the input processing and signal processing pathway within the CI sound processor for direct input versus telecoil input. Further research is warranted to replicate these findings with a larger sample size and to develop and validate a more objective approach to fitting FM systems to CI sound processors. American Academy of Audiology.

Phonological mismatch makes aided speech recognition in noise cognitively taxing.

PubMed

Rudner, Mary; Foo, Catharina; Rönnberg, Jerker; Lunner, Thomas

2007-12-01

The working memory framework for Ease of Language Understanding predicts that speech processing becomes more effortful, thus requiring more explicit cognitive resources, when there is mismatch between speech input and phonological representations in long-term memory. To test this prediction, we changed the compression release settings in the hearing instruments of experienced users and allowed them to train for 9 weeks with the new settings. After training, aided speech recognition in noise was tested with both the trained settings and orthogonal settings. We postulated that training would lead to acclimatization to the trained setting, which in turn would involve establishment of new phonological representations in long-term memory. Further, we postulated that after training, testing with orthogonal settings would give rise to phonological mismatch, associated with more explicit cognitive processing. Thirty-two participants (mean=70.3 years, SD=7.7) with bilateral sensorineural hearing loss (pure-tone average=46.0 dB HL, SD=6.5), bilaterally fitted for more than 1 year with digital, two-channel, nonlinear signal processing hearing instruments and chosen from the patient population at the Linköping University Hospital were randomly assigned to 9 weeks training with new, fast (40 ms) or slow (640 ms), compression release settings in both channels. Aided speech recognition in noise performance was tested according to a design with three within-group factors: test occasion (T1, T2), test setting (fast, slow), and type of noise (unmodulated, modulated) and one between-group factor: experience setting (fast, slow) for two types of speech materials-the highly constrained Hagerman sentences and the less-predictable Hearing in Noise Test (HINT). Complex cognitive capacity was measured using the reading span and letter monitoring tests. PREDICTION: We predicted that speech recognition in noise at T2 with mismatched experience and test settings would be associated with more explicit cognitive processing and thus stronger correlations with complex cognitive measures, as well as poorer performance if complex cognitive capacity was exceeded. Under mismatch conditions, stronger correlations were found between performance on speech recognition with the Hagerman sentences and reading span, along with poorer speech recognition for participants with low reading span scores. No consistent mismatch effect was found with HINT. The mismatch prediction generated by the working memory framework for Ease of Language Understanding is supported for speech recognition in noise with the highly constrained Hagerman sentences but not the less-predictable HINT.

Effects of Within-Talker Variability on Speech Intelligibility in Mandarin-Speaking Adult and Pediatric Cochlear Implant Patients

PubMed Central

Su, Qiaotong; Galvin, John J.; Zhang, Guoping; Li, Yongxin

2016-01-01

Cochlear implant (CI) speech performance is typically evaluated using well-enunciated speech produced at a normal rate by a single talker. CI users often have greater difficulty with variations in speech production encountered in everyday listening. Within a single talker, speaking rate, amplitude, duration, and voice pitch information may be quite variable, depending on the production context. The coarse spectral resolution afforded by the CI limits perception of voice pitch, which is an important cue for speech prosody and for tonal languages such as Mandarin Chinese. In this study, sentence recognition from the Mandarin speech perception database was measured in adult and pediatric Mandarin-speaking CI listeners for a variety of speaking styles: voiced speech produced at slow, normal, and fast speaking rates; whispered speech; voiced emotional speech; and voiced shouted speech. Recognition of Mandarin Hearing in Noise Test sentences was also measured. Results showed that performance was significantly poorer with whispered speech relative to the other speaking styles and that performance was significantly better with slow speech than with fast or emotional speech. Results also showed that adult and pediatric performance was significantly poorer with Mandarin Hearing in Noise Test than with Mandarin speech perception sentences at the normal rate. The results suggest that adult and pediatric Mandarin-speaking CI patients are highly susceptible to whispered speech, due to the lack of lexically important voice pitch cues and perhaps other qualities associated with whispered speech. The results also suggest that test materials may contribute to differences in performance observed between adult and pediatric CI users. PMID:27363714

Performance Evaluation of Speech Recognition Systems as a Next-Generation Pilot-Vehicle Interface Technology

NASA Technical Reports Server (NTRS)

Arthur, Jarvis J., III; Shelton, Kevin J.; Prinzel, Lawrence J., III; Bailey, Randall E.

2016-01-01

During the flight trials known as Gulfstream-V Synthetic Vision Systems Integrated Technology Evaluation (GV-SITE), a Speech Recognition System (SRS) was used by the evaluation pilots. The SRS system was intended to be an intuitive interface for display control (rather than knobs, buttons, etc.). This paper describes the performance of the current "state of the art" Speech Recognition System (SRS). The commercially available technology was evaluated as an application for possible inclusion in commercial aircraft flight decks as a crew-to-vehicle interface. Specifically, the technology is to be used as an interface from aircrew to the onboard displays, controls, and flight management tasks. A flight test of a SRS as well as a laboratory test was conducted.

Modelling Errors in Automatic Speech Recognition for Dysarthric Speakers

NASA Astrophysics Data System (ADS)

Caballero Morales, Santiago Omar; Cox, Stephen J.

2009-12-01

Dysarthria is a motor speech disorder characterized by weakness, paralysis, or poor coordination of the muscles responsible for speech. Although automatic speech recognition (ASR) systems have been developed for disordered speech, factors such as low intelligibility and limited phonemic repertoire decrease speech recognition accuracy, making conventional speaker adaptation algorithms perform poorly on dysarthric speakers. In this work, rather than adapting the acoustic models, we model the errors made by the speaker and attempt to correct them. For this task, two techniques have been developed: (1) a set of "metamodels" that incorporate a model of the speaker's phonetic confusion matrix into the ASR process; (2) a cascade of weighted finite-state transducers at the confusion matrix, word, and language levels. Both techniques attempt to correct the errors made at the phonetic level and make use of a language model to find the best estimate of the correct word sequence. Our experiments show that both techniques outperform standard adaptation techniques.

Voice gender discrimination provides a measure of more than pitch-related perception in cochlear implant users.

PubMed

Li, Tianhao; Fu, Qian-Jie

2011-08-01

(1) To investigate whether voice gender discrimination (VGD) could be a useful indicator of the spectral and temporal processing abilities of individual cochlear implant (CI) users; (2) To examine the relationship between VGD and speech recognition with CI when comparable acoustic cues are used for both perception processes. VGD was measured using two talker sets with different inter-gender fundamental frequencies (F(0)), as well as different acoustic CI simulations. Vowel and consonant recognition in quiet and noise were also measured and compared with VGD performance. Eleven postlingually deaf CI users. The results showed that (1) mean VGD performance differed for different stimulus sets, (2) VGD and speech recognition performance varied among individual CI users, and (3) individual VGD performance was significantly correlated with speech recognition performance under certain conditions. VGD measured with selected stimulus sets might be useful for assessing not only pitch-related perception, but also spectral and temporal processing by individual CI users. In addition to improvements in spectral resolution and modulation detection, the improvement in higher modulation frequency discrimination might be particularly important for CI users in noisy environments.

Implementation of the Intelligent Voice System for Kazakh

NASA Astrophysics Data System (ADS)

Yessenbayev, Zh; Saparkhojayev, N.; Tibeyev, T.

2014-04-01

Modern speech technologies are highly advanced and widely used in day-to-day applications. However, this is mostly concerned with the languages of well-developed countries such as English, German, Japan, Russian, etc. As for Kazakh, the situation is less prominent and research in this field is only starting to evolve. In this research and application-oriented project, we introduce an intelligent voice system for the fast deployment of call-centers and information desks supporting Kazakh speech. The demand on such a system is obvious if the country's large size and small population is considered. The landline and cell phones become the only means of communication for the distant villages and suburbs. The system features Kazakh speech recognition and synthesis modules as well as a web-GUI for efficient dialog management. For speech recognition we use CMU Sphinx engine and for speech synthesis- MaryTTS. The web-GUI is implemented in Java enabling operators to quickly create and manage the dialogs in user-friendly graphical environment. The call routines are handled by Asterisk PBX and JBoss Application Server. The system supports such technologies and protocols as VoIP, VoiceXML, FastAGI, Java SpeechAPI and J2EE. For the speech recognition experiments we compiled and used the first Kazakh speech corpus with the utterances from 169 native speakers. The performance of the speech recognizer is 4.1% WER on isolated word recognition and 6.9% WER on clean continuous speech recognition tasks. The speech synthesis experiments include the training of male and female voices.

Speech variability effects on recognition accuracy associated with concurrent task performance by pilots

NASA Technical Reports Server (NTRS)

Simpson, C. A.

1985-01-01

In the present study of the responses of pairs of pilots to aircraft warning classification tasks using an isolated word, speaker-dependent speech recognition system, the induced stress was manipulated by means of different scoring procedures for the classification task and by the inclusion of a competitive manual control task. Both speech patterns and recognition accuracy were analyzed, and recognition errors were recorded by type for an isolated word speaker-dependent system and by an offline technique for a connected word speaker-dependent system. While errors increased with task loading for the isolated word system, there was no such effect for task loading in the case of the connected word system.

Processing Electromyographic Signals to Recognize Words

NASA Technical Reports Server (NTRS)

Jorgensen, C. C.; Lee, D. D.

2009-01-01

A recently invented speech-recognition method applies to words that are articulated by means of the tongue and throat muscles but are otherwise not voiced or, at most, are spoken sotto voce. This method could satisfy a need for speech recognition under circumstances in which normal audible speech is difficult, poses a hazard, is disturbing to listeners, or compromises privacy. The method could also be used to augment traditional speech recognition by providing an additional source of information about articulator activity. The method can be characterized as intermediate between (1) conventional speech recognition through processing of voice sounds and (2) a method, not yet developed, of processing electroencephalographic signals to extract unspoken words directly from thoughts. This method involves computational processing of digitized electromyographic (EMG) signals from muscle innervation acquired by surface electrodes under a subject's chin near the tongue and on the side of the subject s throat near the larynx. After preprocessing, digitization, and feature extraction, EMG signals are processed by a neural-network pattern classifier, implemented in software, that performs the bulk of the recognition task as described.

Connected word recognition using a cascaded neuro-computational model

NASA Astrophysics Data System (ADS)

Hoya, Tetsuya; van Leeuwen, Cees

2016-10-01

We propose a novel framework for processing a continuous speech stream that contains a varying number of words, as well as non-speech periods. Speech samples are segmented into word-tokens and non-speech periods. An augmented version of an earlier-proposed, cascaded neuro-computational model is used for recognising individual words within the stream. Simulation studies using both a multi-speaker-dependent and speaker-independent digit string database show that the proposed method yields a recognition performance comparable to that obtained by a benchmark approach using hidden Markov models with embedded training.

An audiovisual emotion recognition system

NASA Astrophysics Data System (ADS)

Han, Yi; Wang, Guoyin; Yang, Yong; He, Kun

2007-12-01

Human emotions could be expressed by many bio-symbols. Speech and facial expression are two of them. They are both regarded as emotional information which is playing an important role in human-computer interaction. Based on our previous studies on emotion recognition, an audiovisual emotion recognition system is developed and represented in this paper. The system is designed for real-time practice, and is guaranteed by some integrated modules. These modules include speech enhancement for eliminating noises, rapid face detection for locating face from background image, example based shape learning for facial feature alignment, and optical flow based tracking algorithm for facial feature tracking. It is known that irrelevant features and high dimensionality of the data can hurt the performance of classifier. Rough set-based feature selection is a good method for dimension reduction. So 13 speech features out of 37 ones and 10 facial features out of 33 ones are selected to represent emotional information, and 52 audiovisual features are selected due to the synchronization when speech and video fused together. The experiment results have demonstrated that this system performs well in real-time practice and has high recognition rate. Our results also show that the work in multimodules fused recognition will become the trend of emotion recognition in the future.

Robotics control using isolated word recognition of voice input

NASA Technical Reports Server (NTRS)

Weiner, J. M.

1977-01-01

A speech input/output system is presented that can be used to communicate with a task oriented system. Human speech commands and synthesized voice output extend conventional information exchange capabilities between man and machine by utilizing audio input and output channels. The speech input facility is comprised of a hardware feature extractor and a microprocessor implemented isolated word or phrase recognition system. The recognizer offers a medium sized (100 commands), syntactically constrained vocabulary, and exhibits close to real time performance. The major portion of the recognition processing required is accomplished through software, minimizing the complexity of the hardware feature extractor.

Multisensory speech perception in autism spectrum disorder: From phoneme to whole-word perception.

PubMed

Stevenson, Ryan A; Baum, Sarah H; Segers, Magali; Ferber, Susanne; Barense, Morgan D; Wallace, Mark T

2017-07-01

Speech perception in noisy environments is boosted when a listener can see the speaker's mouth and integrate the auditory and visual speech information. Autistic children have a diminished capacity to integrate sensory information across modalities, which contributes to core symptoms of autism, such as impairments in social communication. We investigated the abilities of autistic and typically-developing (TD) children to integrate auditory and visual speech stimuli in various signal-to-noise ratios (SNR). Measurements of both whole-word and phoneme recognition were recorded. At the level of whole-word recognition, autistic children exhibited reduced performance in both the auditory and audiovisual modalities. Importantly, autistic children showed reduced behavioral benefit from multisensory integration with whole-word recognition, specifically at low SNRs. At the level of phoneme recognition, autistic children exhibited reduced performance relative to their TD peers in auditory, visual, and audiovisual modalities. However, and in contrast to their performance at the level of whole-word recognition, both autistic and TD children showed benefits from multisensory integration for phoneme recognition. In accordance with the principle of inverse effectiveness, both groups exhibited greater benefit at low SNRs relative to high SNRs. Thus, while autistic children showed typical multisensory benefits during phoneme recognition, these benefits did not translate to typical multisensory benefit of whole-word recognition in noisy environments. We hypothesize that sensory impairments in autistic children raise the SNR threshold needed to extract meaningful information from a given sensory input, resulting in subsequent failure to exhibit behavioral benefits from additional sensory information at the level of whole-word recognition. Autism Res 2017. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 1280-1290. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Incorporating Speech Recognition into a Natural User Interface

NASA Technical Reports Server (NTRS)

Chapa, Nicholas

2017-01-01

The Augmented/ Virtual Reality (AVR) Lab has been working to study the applicability of recent virtual and augmented reality hardware and software to KSC operations. This includes the Oculus Rift, HTC Vive, Microsoft HoloLens, and Unity game engine. My project in this lab is to integrate voice recognition and voice commands into an easy to modify system that can be added to an existing portion of a Natural User Interface (NUI). A NUI is an intuitive and simple to use interface incorporating visual, touch, and speech recognition. The inclusion of speech recognition capability will allow users to perform actions or make inquiries using only their voice. The simplicity of needing only to speak to control an on-screen object or enact some digital action means that any user can quickly become accustomed to using this system. Multiple programs were tested for use in a speech command and recognition system. Sphinx4 translates speech to text using a Hidden Markov Model (HMM) based Language Model, an Acoustic Model, and a word Dictionary running on Java. PocketSphinx had similar functionality to Sphinx4 but instead ran on C. However, neither of these programs were ideal as building a Java or C wrapper slowed performance. The most ideal speech recognition system tested was the Unity Engine Grammar Recognizer. A Context Free Grammar (CFG) structure is written in an XML file to specify the structure of phrases and words that will be recognized by Unity Grammar Recognizer. Using Speech Recognition Grammar Specification (SRGS) 1.0 makes modifying the recognized combinations of words and phrases very simple and quick to do. With SRGS 1.0, semantic information can also be added to the XML file, which allows for even more control over how spoken words and phrases are interpreted by Unity. Additionally, using a CFG with SRGS 1.0 produces a Finite State Machine (FSM) functionality limiting the potential for incorrectly heard words or phrases. The purpose of my project was to investigate options for a Speech Recognition System. To that end I attempted to integrate Sphinx4 into a user interface. Sphinx4 had great accuracy and is the only free program able to perform offline speech dictation. However it had a limited dictionary of words that could be recognized, single syllable words were almost impossible for it to hear, and since it ran on Java it could not be integrated into the Unity based NUI. PocketSphinx ran much faster than Sphinx4 which would've made it ideal as a plugin to the Unity NUI, unfortunately creating a C# wrapper for the C code made the program unusable with Unity due to the wrapper slowing code execution and class files becoming unreachable. Unity Grammar Recognizer is the ideal speech recognition interface, it is flexible in recognizing multiple variations of the same command. It is also the most accurate program in recognizing speech due to using an XML grammar to specify speech structure instead of relying solely on a Dictionary and Language model. The Unity Grammar Recognizer will be used with the NUI for these reasons as well as being written in C# which further simplifies the incorporation.

Hybrid simulated annealing and its application to optimization of hidden Markov models for visual speech recognition.

PubMed

Lee, Jong-Seok; Park, Cheol Hoon

2010-08-01

We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is combined with a local optimization operator that substitutes a better solution for the current one to improve the convergence speed and the quality of solutions. We mathematically prove that the sequence of the objective values converges in probability to the global optimum in the algorithm. The algorithm is applied to train HMMs that are used as visual speech recognizers. While the popular training method of HMMs, the expectation-maximization algorithm, achieves only local optima in the parameter space, the proposed method can perform global optimization of the parameters of HMMs and thereby obtain solutions yielding improved recognition performance. The superiority of the proposed algorithm to the conventional ones is demonstrated via isolated word recognition experiments.

A Pilot Investigation regarding Speech-Recognition Performance in Noise for Adults with Hearing Loss in the FM+HA Listening Condition

ERIC Educational Resources Information Center

Lewis, M. Samantha; Gallun, Frederick J.; Gordon, Jane; Lilly, David J.; Crandell, Carl

2010-01-01

While the concurrent use of the hearing aid (HA) microphone with frequency modulation (FM) technology can decrease speech-recognition performance, the FM+HA condition is still an important setting for users of both HA and FM technology. The primary goal of this investigation was to evaluate the effect of attenuating HA gain in the FM+HA listening…

Restoring the missing features of the corrupted speech using linear interpolation methods

NASA Astrophysics Data System (ADS)

Rassem, Taha H.; Makbol, Nasrin M.; Hasan, Ali Muttaleb; Zaki, Siti Syazni Mohd; Girija, P. N.

2017-10-01

One of the main challenges in the Automatic Speech Recognition (ASR) is the noise. The performance of the ASR system reduces significantly if the speech is corrupted by noise. In spectrogram representation of a speech signal, after deleting low Signal to Noise Ratio (SNR) elements, the incomplete spectrogram is obtained. In this case, the speech recognizer should make modifications to the spectrogram in order to restore the missing elements, which is one direction. In another direction, speech recognizer should be able to restore the missing elements due to deleting low SNR elements before performing the recognition. This is can be done using different spectrogram reconstruction methods. In this paper, the geometrical spectrogram reconstruction methods suggested by some researchers are implemented as a toolbox. In these geometrical reconstruction methods, the linear interpolation along time or frequency methods are used to predict the missing elements between adjacent observed elements in the spectrogram. Moreover, a new linear interpolation method using time and frequency together is presented. The CMU Sphinx III software is used in the experiments to test the performance of the linear interpolation reconstruction method. The experiments are done under different conditions such as different lengths of the window and different lengths of utterances. Speech corpus consists of 20 males and 20 females; each one has two different utterances are used in the experiments. As a result, 80% recognition accuracy is achieved with 25% SNR ratio.

On the Use of Evolutionary Algorithms to Improve the Robustness of Continuous Speech Recognition Systems in Adverse Conditions

NASA Astrophysics Data System (ADS)

Selouani, Sid-Ahmed; O'Shaughnessy, Douglas

2003-12-01

Limiting the decrease in performance due to acoustic environment changes remains a major challenge for continuous speech recognition (CSR) systems. We propose a novel approach which combines the Karhunen-Loève transform (KLT) in the mel-frequency domain with a genetic algorithm (GA) to enhance the data representing corrupted speech. The idea consists of projecting noisy speech parameters onto the space generated by the genetically optimized principal axis issued from the KLT. The enhanced parameters increase the recognition rate for highly interfering noise environments. The proposed hybrid technique, when included in the front-end of an HTK-based CSR system, outperforms that of the conventional recognition process in severe interfering car noise environments for a wide range of signal-to-noise ratios (SNRs) varying from 16 dB to[InlineEquation not available: see fulltext.] dB. We also showed the effectiveness of the KLT-GA method in recognizing speech subject to telephone channel degradations.

Automatic Speech Recognition Technology as an Effective Means for Teaching Pronunciation

ERIC Educational Resources Information Center

Elimat, Amal Khalil; AbuSeileek, Ali Farhan

2014-01-01

This study aimed to explore the effect of using automatic speech recognition technology (ASR) on the third grade EFL students' performance in pronunciation, whether teaching pronunciation through ASR is better than regular instruction, and the most effective teaching technique (individual work, pair work, or group work) in teaching pronunciation…

Evaluating Automatic Speech Recognition-Based Language Learning Systems: A Case Study

ERIC Educational Resources Information Center

van Doremalen, Joost; Boves, Lou; Colpaert, Jozef; Cucchiarini, Catia; Strik, Helmer

2016-01-01

The purpose of this research was to evaluate a prototype of an automatic speech recognition (ASR)-based language learning system that provides feedback on different aspects of speaking performance (pronunciation, morphology and syntax) to students of Dutch as a second language. We carried out usability reviews, expert reviews and user tests to…

Technological evaluation of gesture and speech interfaces for enabling dismounted soldier-robot dialogue

NASA Astrophysics Data System (ADS)

Kattoju, Ravi Kiran; Barber, Daniel J.; Abich, Julian; Harris, Jonathan

2016-05-01

With increasing necessity for intuitive Soldier-robot communication in military operations and advancements in interactive technologies, autonomous robots have transitioned from assistance tools to functional and operational teammates able to service an array of military operations. Despite improvements in gesture and speech recognition technologies, their effectiveness in supporting Soldier-robot communication is still uncertain. The purpose of the present study was to evaluate the performance of gesture and speech interface technologies to facilitate Soldier-robot communication during a spatial-navigation task with an autonomous robot. Gesture and speech semantically based spatial-navigation commands leveraged existing lexicons for visual and verbal communication from the U.S Army field manual for visual signaling and a previously established Squad Level Vocabulary (SLV). Speech commands were recorded by a Lapel microphone and Microsoft Kinect, and classified by commercial off-the-shelf automatic speech recognition (ASR) software. Visual signals were captured and classified using a custom wireless gesture glove and software. Participants in the experiment commanded a robot to complete a simulated ISR mission in a scaled down urban scenario by delivering a sequence of gesture and speech commands, both individually and simultaneously, to the robot. Performance and reliability of gesture and speech hardware interfaces and recognition tools were analyzed and reported. Analysis of experimental results demonstrated the employed gesture technology has significant potential for enabling bidirectional Soldier-robot team dialogue based on the high classification accuracy and minimal training required to perform gesture commands.

Automatic lip reading by using multimodal visual features

NASA Astrophysics Data System (ADS)

Takahashi, Shohei; Ohya, Jun

2013-12-01

Since long time ago, speech recognition has been researched, though it does not work well in noisy places such as in the car or in the train. In addition, people with hearing-impaired or difficulties in hearing cannot receive benefits from speech recognition. To recognize the speech automatically, visual information is also important. People understand speeches from not only audio information, but also visual information such as temporal changes in the lip shape. A vision based speech recognition method could work well in noisy places, and could be useful also for people with hearing disabilities. In this paper, we propose an automatic lip-reading method for recognizing the speech by using multimodal visual information without using any audio information such as speech recognition. First, the ASM (Active Shape Model) is used to track and detect the face and lip in a video sequence. Second, the shape, optical flow and spatial frequencies of the lip features are extracted from the lip detected by ASM. Next, the extracted multimodal features are ordered chronologically so that Support Vector Machine is performed in order to learn and classify the spoken words. Experiments for classifying several words show promising results of this proposed method.

Optimizing the Combination of Acoustic and Electric Hearing in the Implanted Ear

PubMed Central

Karsten, Sue A.; Turner, Christopher W.; Brown, Carolyn J.; Jeon, Eun Kyung; Abbas, Paul J.; Gantz, Bruce J.

2016-01-01

Objectives The aim of this study was to determine an optimal approach to program combined acoustic plus electric (A+E) hearing devices in the same ear to maximize speech-recognition performance. Design Ten participants with at least 1 year of experience using Nucleus Hybrid (short electrode) A+E devices were evaluated across three different fitting conditions that varied in the frequency ranges assigned to the acoustically and electrically presented portions of the spectrum. Real-ear measurements were used to optimize the acoustic component for each participant, and the acoustic stimulation was then held constant across conditions. The lower boundary of the electric frequency range was systematically varied to create three conditions with respect to the upper boundary of the acoustic spectrum: Meet, Overlap, and Gap programming. Consonant recognition in quiet and speech recognition in competing-talker babble were evaluated after participants were given the opportunity to adapt by using the experimental programs in their typical everyday listening situations. Participants provided subjective ratings and evaluations for each fitting condition. Results There were no significant differences in performance between conditions (Meet, Overlap, Gap) for consonant recognition in quiet. A significant decrement in performance was measured for the Overlap fitting condition for speech recognition in babble. Subjective ratings indicated a significant preference for the Meet fitting regimen. Conclusions Participants using the Hybrid ipsilateral A+E device generally performed better when the acoustic and electric spectra were programmed to meet at a single frequency region, as opposed to a gap or overlap. Although there is no particular advantage for the Meet fitting strategy for recognition of consonants in quiet, the advantage becomes evident for speech recognition in competing-talker babble and in patient preferences. PMID:23059851

The effect of hearing aid technologies on listening in an automobile

PubMed Central

Wu, Yu-Hsiang; Stangl, Elizabeth; Bentler, Ruth A.; Stanziola, Rachel W.

2014-01-01

Background Communication while traveling in an automobile often is very difficult for hearing aid users. This is because the automobile /road noise level is usually high, and listeners/drivers often do not have access to visual cues. Since the talker of interest usually is not located in front of the driver/listener, conventional directional processing that places the directivity beam toward the listener’s front may not be helpful, and in fact, could have a negative impact on speech recognition (when compared to omnidirectional processing). Recently, technologies have become available in commercial hearing aids that are designed to improve speech recognition and/or listening effort in noisy conditions where talkers are located behind or beside the listener. These technologies include (1) a directional microphone system that uses a backward-facing directivity pattern (Back-DIR processing), (2) a technology that transmits audio signals from the ear with the better signal-to-noise ratio (SNR) to the ear with the poorer SNR (Side-Transmission processing), and (3) a signal processing scheme that suppresses the noise at the ear with the poorer SNR (Side-Suppression processing). Purpose The purpose of the current study was to determine the effect of (1) conventional directional microphones and (2) newer signal processing schemes (Back-DIR, Side-Transmission, and Side-Suppression) on listener’s speech recognition performance and preference for communication in a traveling automobile. Research design A single-blinded, repeated-measures design was used. Study Sample Twenty-five adults with bilateral symmetrical sensorineural hearing loss aged 44 through 84 years participated in the study. Data Collection and Analysis The automobile/road noise and sentences of the Connected Speech Test (CST) were recorded through hearing aids in a standard van moving at a speed of 70 miles/hour on a paved highway. The hearing aids were programmed to omnidirectional microphone, conventional adaptive directional microphone, and the three newer schemes. CST sentences were presented from the side and back of the hearing aids, which were placed on the ears of a manikin. The recorded stimuli were presented to listeners via earphones in a sound treated booth to assess speech recognition performance and preference with each programmed condition. Results Compared to omnidirectional microphones, conventional adaptive directional processing had a detrimental effect on speech recognition when speech was presented from the back or side of the listener. Back-DIR and Side-Transmission processing improved speech recognition performance (relative to both omnidirectional and adaptive directional processing) when speech was from the back and side, respectively. The performance with Side-Suppression processing was better than with adaptive directional processing when speech was from the side. The participants’ preferences for a given processing scheme were generally consistent with speech recognition results. Conclusions The finding that performance with adaptive directional processing was poorer than with omnidirectional microphones demonstrates the importance of selecting the correct microphone technology for different listening situations. The results also suggest the feasibility of using hearing aid technologies to provide a better listening experience for hearing aid users in automobiles. PMID:23886425

Robust recognition of loud and Lombard speech in the fighter cockpit environment

NASA Astrophysics Data System (ADS)

Stanton, Bill J., Jr.

1988-08-01

There are a number of challenges associated with incorporating speech recognition technology into the fighter cockpit. One of the major problems is the wide range of variability in the pilot's voice. That can result from changing levels of stress and workload. Increasing the training set to include abnormal speech is not an attractive option because of the innumerable conditions that would have to be represented and the inordinate amount of time to collect such a training set. A more promising approach is to study subsets of abnormal speech that have been produced under controlled cockpit conditions with the purpose of characterizing reliable shifts that occur relative to normal speech. Such was the initiative of this research. Analyses were conducted for 18 features on 17671 phoneme tokens across eight speakers for normal, loud, and Lombard speech. It was discovered that there was a consistent migration of energy in the sonorants. This discovery of reliable energy shifts led to the development of a method to reduce or eliminate these shifts in the Euclidean distances between LPC log magnitude spectra. This combination significantly improved recognition performance of loud and Lombard speech. Discrepancies in recognition error rates between normal and abnormal speech were reduced by approximately 50 percent for all eight speakers combined.

Age-Related Differences in Listening Effort During Degraded Speech Recognition.

PubMed

Ward, Kristina M; Shen, Jing; Souza, Pamela E; Grieco-Calub, Tina M

The purpose of the present study was to quantify age-related differences in executive control as it relates to dual-task performance, which is thought to represent listening effort, during degraded speech recognition. Twenty-five younger adults (YA; 18-24 years) and 21 older adults (OA; 56-82 years) completed a dual-task paradigm that consisted of a primary speech recognition task and a secondary visual monitoring task. Sentence material in the primary task was either unprocessed or spectrally degraded into 8, 6, or 4 spectral channels using noise-band vocoding. Performance on the visual monitoring task was assessed by the accuracy and reaction time of participants' responses. Performance on the primary and secondary task was quantified in isolation (i.e., single task) and during the dual-task paradigm. Participants also completed a standardized psychometric measure of executive control, including attention and inhibition. Statistical analyses were implemented to evaluate changes in listeners' performance on the primary and secondary tasks (1) per condition (unprocessed vs. vocoded conditions); (2) per task (single task vs. dual task); and (3) per group (YA vs. OA). Speech recognition declined with increasing spectral degradation for both YA and OA when they performed the task in isolation or concurrently with the visual monitoring task. OA were slower and less accurate than YA on the visual monitoring task when performed in isolation, which paralleled age-related differences in standardized scores of executive control. When compared with single-task performance, OA experienced greater declines in secondary-task accuracy, but not reaction time, than YA. Furthermore, results revealed that age-related differences in executive control significantly contributed to age-related differences on the visual monitoring task during the dual-task paradigm. OA experienced significantly greater declines in secondary-task accuracy during degraded speech recognition than YA. These findings are interpreted as suggesting that OA expended greater listening effort than YA, which may be partially attributed to age-related differences in executive control.

Approximated mutual information training for speech recognition using myoelectric signals.

PubMed

Guo, Hua J; Chan, A D C

2006-01-01

A new training algorithm called the approximated maximum mutual information (AMMI) is proposed to improve the accuracy of myoelectric speech recognition using hidden Markov models (HMMs). Previous studies have demonstrated that automatic speech recognition can be performed using myoelectric signals from articulatory muscles of the face. Classification of facial myoelectric signals can be performed using HMMs that are trained using the maximum likelihood (ML) algorithm; however, this algorithm maximizes the likelihood of the observations in the training sequence, which is not directly associated with optimal classification accuracy. The AMMI training algorithm attempts to maximize the mutual information, thereby training the HMMs to optimize their parameters for discrimination. Our results show that AMMI training consistently reduces the error rates compared to these by the ML training, increasing the accuracy by approximately 3% on average.

Effects of Semantic Context and Fundamental Frequency Contours on Mandarin Speech Recognition by Second Language Learners.

PubMed

Zhang, Linjun; Li, Yu; Wu, Han; Li, Xin; Shu, Hua; Zhang, Yang; Li, Ping

2016-01-01

Speech recognition by second language (L2) learners in optimal and suboptimal conditions has been examined extensively with English as the target language in most previous studies. This study extended existing experimental protocols (Wang et al., 2013) to investigate Mandarin speech recognition by Japanese learners of Mandarin at two different levels (elementary vs. intermediate) of proficiency. The overall results showed that in addition to L2 proficiency, semantic context, F0 contours, and listening condition all affected the recognition performance on the Mandarin sentences. However, the effects of semantic context and F0 contours on L2 speech recognition diverged to some extent. Specifically, there was significant modulation effect of listening condition on semantic context, indicating that L2 learners made use of semantic context less efficiently in the interfering background than in quiet. In contrast, no significant modulation effect of listening condition on F0 contours was found. Furthermore, there was significant interaction between semantic context and F0 contours, indicating that semantic context becomes more important for L2 speech recognition when F0 information is degraded. None of these effects were found to be modulated by L2 proficiency. The discrepancy in the effects of semantic context and F0 contours on L2 speech recognition in the interfering background might be related to differences in processing capacities required by the two types of information in adverse listening conditions.

The MIT Summit Speech Recognition System: A Progress Report

DTIC Science & Technology

1989-01-01

understanding of the human communication process. Despite recent development of some speech recognition systems with high accuracy, the performance of such...over the past four decades on human communication , in the hope that such systems will one day have a performance approaching that of humans. We are...optimize its use. Third, the system must have a stochastic component to deal with the present state of ignorance in our understanding of the human

Automatic speech recognition technology development at ITT Defense Communications Division

NASA Technical Reports Server (NTRS)

White, George M.

1977-01-01

An assessment of the applications of automatic speech recognition to defense communication systems is presented. Future research efforts include investigations into the following areas: (1) dynamic programming; (2) recognition of speech degraded by noise; (3) speaker independent recognition; (4) large vocabulary recognition; (5) word spotting and continuous speech recognition; and (6) isolated word recognition.

Relations Between Self-reported Executive Functioning and Speech Perception Skills in Adult Cochlear Implant Users.

PubMed

Moberly, Aaron C; Patel, Tirth R; Castellanos, Irina

2018-02-01

As a result of their hearing loss, adults with cochlear implants (CIs) would self-report poorer executive functioning (EF) skills than normal-hearing (NH) peers, and these EF skills would be associated with performance on speech recognition tasks. EF refers to a group of high order neurocognitive skills responsible for behavioral and emotional regulation during goal-directed activity, and EF has been found to be poorer in children with CIs than their NH age-matched peers. Moreover, there is increasing evidence that neurocognitive skills, including some EF skills, contribute to the ability to recognize speech through a CI. Thirty postlingually deafened adults with CIs and 42 age-matched NH adults were enrolled. Participants and their spouses or significant others (informants) completed well-validated self-reports or informant-reports of EF, the Behavior Rating Inventory of Executive Function - Adult (BRIEF-A). CI users' speech recognition skills were assessed in quiet using several measures of sentence recognition. NH peers were tested for recognition of noise-vocoded versions of the same speech stimuli. CI users self-reported difficulty on EF tasks of shifting and task monitoring. In CI users, measures of speech recognition correlated with several self-reported EF skills. The present findings provide further evidence that neurocognitive factors, including specific EF skills, may decline in association with hearing loss, and that some of these EF skills contribute to speech processing under degraded listening conditions.

Relating dynamic brain states to dynamic machine states: Human and machine solutions to the speech recognition problem

PubMed Central

Liu, Xunying; Zhang, Chao; Woodland, Phil; Fonteneau, Elisabeth

2017-01-01

There is widespread interest in the relationship between the neurobiological systems supporting human cognition and emerging computational systems capable of emulating these capacities. Human speech comprehension, poorly understood as a neurobiological process, is an important case in point. Automatic Speech Recognition (ASR) systems with near-human levels of performance are now available, which provide a computationally explicit solution for the recognition of words in continuous speech. This research aims to bridge the gap between speech recognition processes in humans and machines, using novel multivariate techniques to compare incremental ‘machine states’, generated as the ASR analysis progresses over time, to the incremental ‘brain states’, measured using combined electro- and magneto-encephalography (EMEG), generated as the same inputs are heard by human listeners. This direct comparison of dynamic human and machine internal states, as they respond to the same incrementally delivered sensory input, revealed a significant correspondence between neural response patterns in human superior temporal cortex and the structural properties of ASR-derived phonetic models. Spatially coherent patches in human temporal cortex responded selectively to individual phonetic features defined on the basis of machine-extracted regularities in the speech to lexicon mapping process. These results demonstrate the feasibility of relating human and ASR solutions to the problem of speech recognition, and suggest the potential for further studies relating complex neural computations in human speech comprehension to the rapidly evolving ASR systems that address the same problem domain. PMID:28945744

Studies in automatic speech recognition and its application in aerospace

NASA Astrophysics Data System (ADS)

Taylor, Michael Robinson

Human communication is characterized in terms of the spectral and temporal dimensions of speech waveforms. Electronic speech recognition strategies based on Dynamic Time Warping and Markov Model algorithms are described and typical digit recognition error rates are tabulated. The application of Direct Voice Input (DVI) as an interface between man and machine is explored within the context of civil and military aerospace programmes. Sources of physical and emotional stress affecting speech production within military high performance aircraft are identified. Experimental results are reported which quantify fundamental frequency and coarse temporal dimensions of male speech as a function of the vibration, linear acceleration and noise levels typical of aerospace environments; preliminary indications of acoustic phonetic variability reported by other researchers are summarized. Connected whole-word pattern recognition error rates are presented for digits spoken under controlled Gz sinusoidal whole-body vibration. Correlations are made between significant increases in recognition error rate and resonance of the abdomen-thorax and head subsystems of the body. The phenomenon of vibrato style speech produced under low frequency whole-body Gz vibration is also examined. Interactive DVI system architectures and avionic data bus integration concepts are outlined together with design procedures for the efficient development of pilot-vehicle command and control protocols.

Fifty years of progress in speech and speaker recognition

NASA Astrophysics Data System (ADS)

Furui, Sadaoki

2004-10-01

Speech and speaker recognition technology has made very significant progress in the past 50 years. The progress can be summarized by the following changes: (1) from template matching to corpus-base statistical modeling, e.g., HMM and n-grams, (2) from filter bank/spectral resonance to Cepstral features (Cepstrum + DCepstrum + DDCepstrum), (3) from heuristic time-normalization to DTW/DP matching, (4) from gdistanceh-based to likelihood-based methods, (5) from maximum likelihood to discriminative approach, e.g., MCE/GPD and MMI, (6) from isolated word to continuous speech recognition, (7) from small vocabulary to large vocabulary recognition, (8) from context-independent units to context-dependent units for recognition, (9) from clean speech to noisy/telephone speech recognition, (10) from single speaker to speaker-independent/adaptive recognition, (11) from monologue to dialogue/conversation recognition, (12) from read speech to spontaneous speech recognition, (13) from recognition to understanding, (14) from single-modality (audio signal only) to multi-modal (audio/visual) speech recognition, (15) from hardware recognizer to software recognizer, and (16) from no commercial application to many practical commercial applications. Most of these advances have taken place in both the fields of speech recognition and speaker recognition. The majority of technological changes have been directed toward the purpose of increasing robustness of recognition, including many other additional important techniques not noted above.

Application of speech recognition and synthesis in the general aviation cockpit

NASA Technical Reports Server (NTRS)

North, R. A.; Mountford, S. J.; Bergeron, H.

1984-01-01

Interactive speech recognition/synthesis technology is assessed as a method for the aleviation of single-pilot IFR flight workloads. Attention was given during this series of evaluations to the conditions typical of general aviation twin-engine aircrft cockpits, covering several commonly encountered IFR flight condition scenarios. The most beneficial speech command tasks are noted to be in the data retrieval domain, which would allow the pilot access to uplinked data, checklists, and performance charts. Data entry tasks also appear to benefit from this technology.

Voice gender discrimination provides a measure of more than pitch-related perception in cochlear implant users

PubMed Central

Li, Tianhao; Fu, Qian-Jie

2013-01-01

Objectives (1) To investigate whether voice gender discrimination (VGD) could be a useful indicator of the spectral and temporal processing abilities of individual cochlear implant (CI) users; (2) To examine the relationship between VGD and speech recognition with CI when comparable acoustic cues are used for both perception processes. Design VGD was measured using two talker sets with different inter-gender fundamental frequencies (F0), as well as different acoustic CI simulations. Vowel and consonant recognition in quiet and noise were also measured and compared with VGD performance. Study sample Eleven postlingually deaf CI users. Results The results showed that (1) mean VGD performance differed for different stimulus sets, (2) VGD and speech recognition performance varied among individual CI users, and (3) individual VGD performance was significantly correlated with speech recognition performance under certain conditions. Conclusions VGD measured with selected stimulus sets might be useful for assessing not only pitch-related perception, but also spectral and temporal processing by individual CI users. In addition to improvements in spectral resolution and modulation detection, the improvement in higher modulation frequency discrimination might be particularly important for CI users in noisy environments. PMID:21696330

Influence of auditory attention on sentence recognition captured by the neural phase.

PubMed

Müller, Jana Annina; Kollmeier, Birger; Debener, Stefan; Brand, Thomas

2018-03-07

The aim of this study was to investigate whether attentional influences on speech recognition are reflected in the neural phase entrained by an external modulator. Sentences were presented in 7 Hz sinusoidally modulated noise while the neural response to that modulation frequency was monitored by electroencephalogram (EEG) recordings in 21 participants. We implemented a selective attention paradigm including three different attention conditions while keeping physical stimulus parameters constant. The participants' task was either to repeat the sentence as accurately as possible (speech recognition task), to count the number of decrements implemented in modulated noise (decrement detection task), or to do both (dual task), while the EEG was recorded. Behavioural analysis revealed reduced performance in the dual task condition for decrement detection, possibly reflecting limited cognitive resources. EEG analysis revealed no significant differences in power for the 7 Hz modulation frequency, but an attention-dependent phase difference between tasks. Further phase analysis revealed a significant difference 500 ms after sentence onset between trials with correct and incorrect responses for speech recognition, indicating that speech recognition performance and the neural phase are linked via selective attention mechanisms, at least shortly after sentence onset. However, the neural phase effects identified were small and await further investigation. © 2018 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Speech Recognition of Bimodal Cochlear Implant Recipients Using a Wireless Audio Streaming Accessory for the Telephone.

PubMed

Wolfe, Jace; Morais, Mila; Schafer, Erin

2016-02-01

The goals of the present investigation were (1) to evaluate recognition of recorded speech presented over a mobile telephone for a group of adult bimodal cochlear implant users, and (2) to measure the potential benefits of wireless hearing assistance technology (HAT) for mobile telephone speech recognition using bimodal stimulation (i.e., a cochlear implant in one ear and a hearing aid on the other ear). A three-by-two-way repeated measures design was used to evaluate mobile telephone sentence-recognition performance differences obtained in quiet and in noise with and without the wireless HAT accessory coupled to the hearing aid alone, CI sound processor alone, and in the bimodal condition. Outpatient cochlear implant clinic. Sixteen bimodal users with Nucleus 24, Freedom, CI512, or CI422 cochlear implants participated in this study. Performance was measured with and without the use of a wireless HAT for the telephone used with the hearing aid alone, CI alone, and bimodal condition. CNC word recognition in quiet and in noise with and without the use of a wireless HAT telephone accessory in the hearing aid alone, CI alone, and bimodal conditions. Results suggested that the bimodal condition gave significantly better speech recognition on the mobile telephone with the wireless HAT. A wireless HAT for the mobile telephone provides bimodal users with significant improvement in word recognition in quiet and in noise over the mobile telephone.

Recognition and localization of speech by adult cochlear implant recipients wearing a digital hearing aid in the nonimplanted ear (bimodal hearing).

PubMed

Potts, Lisa G; Skinner, Margaret W; Litovsky, Ruth A; Strube, Michael J; Kuk, Francis

2009-06-01

The use of bilateral amplification is now common clinical practice for hearing aid users but not for cochlear implant recipients. In the past, most cochlear implant recipients were implanted in one ear and wore only a monaural cochlear implant processor. There has been recent interest in benefits arising from bilateral stimulation that may be present for cochlear implant recipients. One option for bilateral stimulation is the use of a cochlear implant in one ear and a hearing aid in the opposite nonimplanted ear (bimodal hearing). This study evaluated the effect of wearing a cochlear implant in one ear and a digital hearing aid in the opposite ear on speech recognition and localization. A repeated-measures correlational study was completed. Nineteen adult Cochlear Nucleus 24 implant recipients participated in the study. The participants were fit with a Widex Senso Vita 38 hearing aid to achieve maximum audibility and comfort within their dynamic range. Soundfield thresholds, loudness growth, speech recognition, localization, and subjective questionnaires were obtained six-eight weeks after the hearing aid fitting. Testing was completed in three conditions: hearing aid only, cochlear implant only, and cochlear implant and hearing aid (bimodal). All tests were repeated four weeks after the first test session. Repeated-measures analysis of variance was used to analyze the data. Significant effects were further examined using pairwise comparison of means or in the case of continuous moderators, regression analyses. The speech-recognition and localization tasks were unique, in that a speech stimulus presented from a variety of roaming azimuths (140 degree loudspeaker array) was used. Performance in the bimodal condition was significantly better for speech recognition and localization compared to the cochlear implant-only and hearing aid-only conditions. Performance was also different between these conditions when the location (i.e., side of the loudspeaker array that presented the word) was analyzed. In the bimodal condition, the speech-recognition and localization tasks were equal regardless of which side of the loudspeaker array presented the word, while performance was significantly poorer for the monaural conditions (hearing aid only and cochlear implant only) when the words were presented on the side with no stimulation. Binaural loudness summation of 1-3 dB was seen in soundfield thresholds and loudness growth in the bimodal condition. Measures of the audibility of sound with the hearing aid, including unaided thresholds, soundfield thresholds, and the Speech Intelligibility Index, were significant moderators of speech recognition and localization. Based on the questionnaire responses, participants showed a strong preference for bimodal stimulation. These findings suggest that a well-fit digital hearing aid worn in conjunction with a cochlear implant is beneficial to speech recognition and localization. The dynamic test procedures used in this study illustrate the importance of bilateral hearing for locating, identifying, and switching attention between multiple speakers. It is recommended that unilateral cochlear implant recipients, with measurable unaided hearing thresholds, be fit with a hearing aid.

Speech Recognition for Medical Dictation: Overview in Quebec and Systematic Review.

PubMed

Poder, Thomas G; Fisette, Jean-François; Déry, Véronique

2018-04-03

Speech recognition is increasingly used in medical reporting. The aim of this article is to identify in the literature the strengths and weaknesses of this technology, as well as barriers to and facilitators of its implementation. A systematic review of systematic reviews was performed using PubMed, Scopus, the Cochrane Library and the Center for Reviews and Dissemination through August 2017. The gray literature has also been consulted. The quality of systematic reviews has been assessed with the AMSTAR checklist. The main inclusion criterion was use of speech recognition for medical reporting (front-end or back-end). A survey has also been conducted in Quebec, Canada, to identify the dissemination of this technology in this province, as well as the factors leading to the success or failure of its implementation. Five systematic reviews were identified. These reviews indicated a high level of heterogeneity across studies. The quality of the studies reported was generally poor. Speech recognition is not as accurate as human transcription, but it can dramatically reduce turnaround times for reporting. In front-end use, medical doctors need to spend more time on dictation and correction than required with human transcription. With speech recognition, major errors occur up to three times more frequently. In back-end use, a potential increase in productivity of transcriptionists was noted. In conclusion, speech recognition offers several advantages for medical reporting. However, these advantages are countered by an increased burden on medical doctors and by risks of additional errors in medical reports. It is also hard to identify for which medical specialties and which clinical activities the use of speech recognition will be the most beneficial.

A novel probabilistic framework for event-based speech recognition

NASA Astrophysics Data System (ADS)

Juneja, Amit; Espy-Wilson, Carol

2003-10-01

One of the reasons for unsatisfactory performance of the state-of-the-art automatic speech recognition (ASR) systems is the inferior acoustic modeling of low-level acoustic-phonetic information in the speech signal. An acoustic-phonetic approach to ASR, on the other hand, explicitly targets linguistic information in the speech signal, but such a system for continuous speech recognition (CSR) is not known to exist. A probabilistic and statistical framework for CSR based on the idea of the representation of speech sounds by bundles of binary valued articulatory phonetic features is proposed. Multiple probabilistic sequences of linguistically motivated landmarks are obtained using binary classifiers of manner phonetic features-syllabic, sonorant and continuant-and the knowledge-based acoustic parameters (APs) that are acoustic correlates of those features. The landmarks are then used for the extraction of knowledge-based APs for source and place phonetic features and their binary classification. Probabilistic landmark sequences are constrained using manner class language models for isolated or connected word recognition. The proposed method could overcome the disadvantages encountered by the early acoustic-phonetic knowledge-based systems that led the ASR community to switch to systems highly dependent on statistical pattern analysis methods and probabilistic language or grammar models.

Hemispheric lateralization of linguistic prosody recognition in comparison to speech and speaker recognition.

PubMed

Kreitewolf, Jens; Friederici, Angela D; von Kriegstein, Katharina

2014-11-15

Hemispheric specialization for linguistic prosody is a controversial issue. While it is commonly assumed that linguistic prosody and emotional prosody are preferentially processed in the right hemisphere, neuropsychological work directly comparing processes of linguistic prosody and emotional prosody suggests a predominant role of the left hemisphere for linguistic prosody processing. Here, we used two functional magnetic resonance imaging (fMRI) experiments to clarify the role of left and right hemispheres in the neural processing of linguistic prosody. In the first experiment, we sought to confirm previous findings showing that linguistic prosody processing compared to other speech-related processes predominantly involves the right hemisphere. Unlike previous studies, we controlled for stimulus influences by employing a prosody and speech task using the same speech material. The second experiment was designed to investigate whether a left-hemispheric involvement in linguistic prosody processing is specific to contrasts between linguistic prosody and emotional prosody or whether it also occurs when linguistic prosody is contrasted against other non-linguistic processes (i.e., speaker recognition). Prosody and speaker tasks were performed on the same stimulus material. In both experiments, linguistic prosody processing was associated with activity in temporal, frontal, parietal and cerebellar regions. Activation in temporo-frontal regions showed differential lateralization depending on whether the control task required recognition of speech or speaker: recognition of linguistic prosody predominantly involved right temporo-frontal areas when it was contrasted against speech recognition; when contrasted against speaker recognition, recognition of linguistic prosody predominantly involved left temporo-frontal areas. The results show that linguistic prosody processing involves functions of both hemispheres and suggest that recognition of linguistic prosody is based on an inter-hemispheric mechanism which exploits both a right-hemispheric sensitivity to pitch information and a left-hemispheric dominance in speech processing. Copyright © 2014 Elsevier Inc. All rights reserved.

Speech Clarity Index (Ψ): A Distance-Based Speech Quality Indicator and Recognition Rate Prediction for Dysarthric Speakers with Cerebral Palsy

NASA Astrophysics Data System (ADS)

Kayasith, Prakasith; Theeramunkong, Thanaruk

It is a tedious and subjective task to measure severity of a dysarthria by manually evaluating his/her speech using available standard assessment methods based on human perception. This paper presents an automated approach to assess speech quality of a dysarthric speaker with cerebral palsy. With the consideration of two complementary factors, speech consistency and speech distinction, a speech quality indicator called speech clarity index (Ψ) is proposed as a measure of the speaker's ability to produce consistent speech signal for a certain word and distinguished speech signal for different words. As an application, it can be used to assess speech quality and forecast speech recognition rate of speech made by an individual dysarthric speaker before actual exhaustive implementation of an automatic speech recognition system for the speaker. The effectiveness of Ψ as a speech recognition rate predictor is evaluated by rank-order inconsistency, correlation coefficient, and root-mean-square of difference. The evaluations had been done by comparing its predicted recognition rates with ones predicted by the standard methods called the articulatory and intelligibility tests based on the two recognition systems (HMM and ANN). The results show that Ψ is a promising indicator for predicting recognition rate of dysarthric speech. All experiments had been done on speech corpus composed of speech data from eight normal speakers and eight dysarthric speakers.

Investigating the Effectiveness of Speech-To-Text Recognition Applications on Learning Performance, Attention, and Meditation

ERIC Educational Resources Information Center

Shadiev, Rustam; Huang, Yueh-Min; Hwang, Jan-Pan

2017-01-01

In this study, the effectiveness of the application of speech-to-text recognition (STR) technology on enhancing learning and concentration in a calm state of mind, hereafter referred to as meditation (An intentional and self-regulated focusing of attention in order to relax and calm the mind), was investigated. This effectiveness was further…

Emotion recognition from speech: tools and challenges

NASA Astrophysics Data System (ADS)

Al-Talabani, Abdulbasit; Sellahewa, Harin; Jassim, Sabah A.

2015-05-01

Human emotion recognition from speech is studied frequently for its importance in many applications, e.g. human-computer interaction. There is a wide diversity and non-agreement about the basic emotion or emotion-related states on one hand and about where the emotion related information lies in the speech signal on the other side. These diversities motivate our investigations into extracting Meta-features using the PCA approach, or using a non-adaptive random projection RP, which significantly reduce the large dimensional speech feature vectors that may contain a wide range of emotion related information. Subsets of Meta-features are fused to increase the performance of the recognition model that adopts the score-based LDC classifier. We shall demonstrate that our scheme outperform the state of the art results when tested on non-prompted databases or acted databases (i.e. when subjects act specific emotions while uttering a sentence). However, the huge gap between accuracy rates achieved on the different types of datasets of speech raises questions about the way emotions modulate the speech. In particular we shall argue that emotion recognition from speech should not be dealt with as a classification problem. We shall demonstrate the presence of a spectrum of different emotions in the same speech portion especially in the non-prompted data sets, which tends to be more "natural" than the acted datasets where the subjects attempt to suppress all but one emotion.

A new time-adaptive discrete bionic wavelet transform for enhancing speech from adverse noise environment

NASA Astrophysics Data System (ADS)

Palaniswamy, Sumithra; Duraisamy, Prakash; Alam, Mohammad Showkat; Yuan, Xiaohui

2012-04-01

Automatic speech processing systems are widely used in everyday life such as mobile communication, speech and speaker recognition, and for assisting the hearing impaired. In speech communication systems, the quality and intelligibility of speech is of utmost importance for ease and accuracy of information exchange. To obtain an intelligible speech signal and one that is more pleasant to listen, noise reduction is essential. In this paper a new Time Adaptive Discrete Bionic Wavelet Thresholding (TADBWT) scheme is proposed. The proposed technique uses Daubechies mother wavelet to achieve better enhancement of speech from additive non- stationary noises which occur in real life such as street noise and factory noise. Due to the integration of human auditory system model into the wavelet transform, bionic wavelet transform (BWT) has great potential for speech enhancement which may lead to a new path in speech processing. In the proposed technique, at first, discrete BWT is applied to noisy speech to derive TADBWT coefficients. Then the adaptive nature of the BWT is captured by introducing a time varying linear factor which updates the coefficients at each scale over time. This approach has shown better performance than the existing algorithms at lower input SNR due to modified soft level dependent thresholding on time adaptive coefficients. The objective and subjective test results confirmed the competency of the TADBWT technique. The effectiveness of the proposed technique is also evaluated for speaker recognition task under noisy environment. The recognition results show that the TADWT technique yields better performance when compared to alternate methods specifically at lower input SNR.

SAM: speech-aware applications in medicine to support structured data entry.

PubMed Central

Wormek, A. K.; Ingenerf, J.; Orthner, H. F.

1997-01-01

In the last two years, improvement in speech recognition technology has directed the medical community's interest to porting and using such innovations in clinical systems. The acceptance of speech recognition systems in clinical domains increases with recognition speed, large medical vocabulary, high accuracy, continuous speech recognition, and speaker independence. Although some commercial speech engines approach these requirements, the greatest benefit can be achieved in adapting a speech recognizer to a specific medical application. The goals of our work are first, to develop a speech-aware core component which is able to establish connections to speech recognition engines of different vendors. This is realized in SAM. Second, with applications based on SAM we want to support the physician in his/her routine clinical care activities. Within the STAMP project (STAndardized Multimedia report generator in Pathology), we extend SAM by combining a structured data entry approach with speech recognition technology. Another speech-aware application in the field of Diabetes care is connected to a terminology server. The server delivers a controlled vocabulary which can be used for speech recognition. PMID:9357730

How linguistic closure and verbal working memory relate to speech recognition in noise--a review.

PubMed

Besser, Jana; Koelewijn, Thomas; Zekveld, Adriana A; Kramer, Sophia E; Festen, Joost M

2013-06-01

The ability to recognize masked speech, commonly measured with a speech reception threshold (SRT) test, is associated with cognitive processing abilities. Two cognitive factors frequently assessed in speech recognition research are the capacity of working memory (WM), measured by means of a reading span (Rspan) or listening span (Lspan) test, and the ability to read masked text (linguistic closure), measured by the text reception threshold (TRT). The current article provides a review of recent hearing research that examined the relationship of TRT and WM span to SRTs in various maskers. Furthermore, modality differences in WM capacity assessed with the Rspan compared to the Lspan test were examined and related to speech recognition abilities in an experimental study with young adults with normal hearing (NH). Span scores were strongly associated with each other, but were higher in the auditory modality. The results of the reviewed studies suggest that TRT and WM span are related to each other, but differ in their relationships with SRT performance. In NH adults of middle age or older, both TRT and Rspan were associated with SRTs in speech maskers, whereas TRT better predicted speech recognition in fluctuating nonspeech maskers. The associations with SRTs in steady-state noise were inconclusive for both measures. WM span was positively related to benefit from contextual information in speech recognition, but better TRTs related to less interference from unrelated cues. Data for individuals with impaired hearing are limited, but larger WM span seems to give a general advantage in various listening situations.

How Linguistic Closure and Verbal Working Memory Relate to Speech Recognition in Noise—A Review

PubMed Central

Koelewijn, Thomas; Zekveld, Adriana A.; Kramer, Sophia E.; Festen, Joost M.

2013-01-01

The ability to recognize masked speech, commonly measured with a speech reception threshold (SRT) test, is associated with cognitive processing abilities. Two cognitive factors frequently assessed in speech recognition research are the capacity of working memory (WM), measured by means of a reading span (Rspan) or listening span (Lspan) test, and the ability to read masked text (linguistic closure), measured by the text reception threshold (TRT). The current article provides a review of recent hearing research that examined the relationship of TRT and WM span to SRTs in various maskers. Furthermore, modality differences in WM capacity assessed with the Rspan compared to the Lspan test were examined and related to speech recognition abilities in an experimental study with young adults with normal hearing (NH). Span scores were strongly associated with each other, but were higher in the auditory modality. The results of the reviewed studies suggest that TRT and WM span are related to each other, but differ in their relationships with SRT performance. In NH adults of middle age or older, both TRT and Rspan were associated with SRTs in speech maskers, whereas TRT better predicted speech recognition in fluctuating nonspeech maskers. The associations with SRTs in steady-state noise were inconclusive for both measures. WM span was positively related to benefit from contextual information in speech recognition, but better TRTs related to less interference from unrelated cues. Data for individuals with impaired hearing are limited, but larger WM span seems to give a general advantage in various listening situations. PMID:23945955

A multi-views multi-learners approach towards dysarthric speech recognition using multi-nets artificial neural networks.

PubMed

Shahamiri, Seyed Reza; Salim, Siti Salwah Binti

2014-09-01

Automatic speech recognition (ASR) can be very helpful for speakers who suffer from dysarthria, a neurological disability that damages the control of motor speech articulators. Although a few attempts have been made to apply ASR technologies to sufferers of dysarthria, previous studies show that such ASR systems have not attained an adequate level of performance. In this study, a dysarthric multi-networks speech recognizer (DM-NSR) model is provided using a realization of multi-views multi-learners approach called multi-nets artificial neural networks, which tolerates variability of dysarthric speech. In particular, the DM-NSR model employs several ANNs (as learners) to approximate the likelihood of ASR vocabulary words and to deal with the complexity of dysarthric speech. The proposed DM-NSR approach was presented as both speaker-dependent and speaker-independent paradigms. In order to highlight the performance of the proposed model over legacy models, multi-views single-learner models of the DM-NSRs were also provided and their efficiencies were compared in detail. Moreover, a comparison among the prominent dysarthric ASR methods and the proposed one is provided. The results show that the DM-NSR recorded improved recognition rate by up to 24.67% and the error rate was reduced by up to 8.63% over the reference model.

The Benefits of Residual Hair Cell Function for Speech and Music Perception in Pediatric Bimodal Cochlear Implant Listeners.

PubMed

Cheng, Xiaoting; Liu, Yangwenyi; Wang, Bing; Yuan, Yasheng; Galvin, John J; Fu, Qian-Jie; Shu, Yilai; Chen, Bing

2018-01-01

The aim of this study was to investigate the benefits of residual hair cell function for speech and music perception in bimodal pediatric Mandarin-speaking cochlear implant (CI) listeners. Speech and music performance was measured in 35 Mandarin-speaking pediatric CI users for unilateral (CI-only) and bimodal listening. Mandarin speech perception was measured for vowels, consonants, lexical tones, and sentences in quiet. Music perception was measured for melodic contour identification (MCI). Combined electric and acoustic hearing significantly improved MCI and Mandarin tone recognition performance, relative to CI-only performance. For MCI, performance was significantly better with bimodal listening for all semitone spacing conditions ( p < 0.05 in all cases). For tone recognition, bimodal performance was significantly better only for tone 2 (rising; p < 0.05). There were no significant differences between CI-only and CI + HA for vowel, consonant, or sentence recognition. The results suggest that combined electric and acoustic hearing can significantly improve perception of music and Mandarin tones in pediatric Mandarin-speaking CI patients. Music and lexical tone perception depends strongly on pitch perception, and the contralateral acoustic hearing coming from residual hair cell function provided pitch cues that are generally not well preserved in electric hearing.

Not all sounds sound the same: Parkinson's disease affects differently emotion processing in music and in speech prosody.

PubMed

Lima, César F; Garrett, Carolina; Castro, São Luís

2013-01-01

Does emotion processing in music and speech prosody recruit common neurocognitive mechanisms? To examine this question, we implemented a cross-domain comparative design in Parkinson's disease (PD). Twenty-four patients and 25 controls performed emotion recognition tasks for music and spoken sentences. In music, patients had impaired recognition of happiness and peacefulness, and intact recognition of sadness and fear; this pattern was independent of general cognitive and perceptual abilities. In speech, patients had a small global impairment, which was significantly mediated by executive dysfunction. Hence, PD affected differently musical and prosodic emotions. This dissociation indicates that the mechanisms underlying the two domains are partly independent.

I Hear You Eat and Speak: Automatic Recognition of Eating Condition and Food Type, Use-Cases, and Impact on ASR Performance

PubMed Central

Hantke, Simone; Weninger, Felix; Kurle, Richard; Ringeval, Fabien; Batliner, Anton; Mousa, Amr El-Desoky; Schuller, Björn

2016-01-01

We propose a new recognition task in the area of computational paralinguistics: automatic recognition of eating conditions in speech, i. e., whether people are eating while speaking, and what they are eating. To this end, we introduce the audio-visual iHEARu-EAT database featuring 1.6 k utterances of 30 subjects (mean age: 26.1 years, standard deviation: 2.66 years, gender balanced, German speakers), six types of food (Apple, Nectarine, Banana, Haribo Smurfs, Biscuit, and Crisps), and read as well as spontaneous speech, which is made publicly available for research purposes. We start with demonstrating that for automatic speech recognition (ASR), it pays off to know whether speakers are eating or not. We also propose automatic classification both by brute-forcing of low-level acoustic features as well as higher-level features related to intelligibility, obtained from an Automatic Speech Recogniser. Prediction of the eating condition was performed with a Support Vector Machine (SVM) classifier employed in a leave-one-speaker-out evaluation framework. Results show that the binary prediction of eating condition (i. e., eating or not eating) can be easily solved independently of the speaking condition; the obtained average recalls are all above 90%. Low-level acoustic features provide the best performance on spontaneous speech, which reaches up to 62.3% average recall for multi-way classification of the eating condition, i. e., discriminating the six types of food, as well as not eating. The early fusion of features related to intelligibility with the brute-forced acoustic feature set improves the performance on read speech, reaching a 66.4% average recall for the multi-way classification task. Analysing features and classifier errors leads to a suitable ordinal scale for eating conditions, on which automatic regression can be performed with up to 56.2% determination coefficient. PMID:27176486

Syntactic error modeling and scoring normalization in speech recognition

NASA Technical Reports Server (NTRS)

Olorenshaw, Lex

1991-01-01

The objective was to develop the speech recognition system to be able to detect speech which is pronounced incorrectly, given that the text of the spoken speech is known to the recognizer. Research was performed in the following areas: (1) syntactic error modeling; (2) score normalization; and (3) phoneme error modeling. The study into the types of errors that a reader makes will provide the basis for creating tests which will approximate the use of the system in the real world. NASA-Johnson will develop this technology into a 'Literacy Tutor' in order to bring innovative concepts to the task of teaching adults to read.

Unvoiced Speech Recognition Using Tissue-Conductive Acoustic Sensor

NASA Astrophysics Data System (ADS)

Heracleous, Panikos; Kaino, Tomomi; Saruwatari, Hiroshi; Shikano, Kiyohiro

2006-12-01

We present the use of stethoscope and silicon NAM (nonaudible murmur) microphones in automatic speech recognition. NAM microphones are special acoustic sensors, which are attached behind the talker's ear and can capture not only normal (audible) speech, but also very quietly uttered speech (nonaudible murmur). As a result, NAM microphones can be applied in automatic speech recognition systems when privacy is desired in human-machine communication. Moreover, NAM microphones show robustness against noise and they might be used in special systems (speech recognition, speech transform, etc.) for sound-impaired people. Using adaptation techniques and a small amount of training data, we achieved for a 20 k dictation task a[InlineEquation not available: see fulltext.] word accuracy for nonaudible murmur recognition in a clean environment. In this paper, we also investigate nonaudible murmur recognition in noisy environments and the effect of the Lombard reflex on nonaudible murmur recognition. We also propose three methods to integrate audible speech and nonaudible murmur recognition using a stethoscope NAM microphone with very promising results.

Speech recognition technology: an outlook for human-to-machine interaction.

PubMed

Erdel, T; Crooks, S

2000-01-01

Speech recognition, as an enabling technology in healthcare-systems computing, is a topic that has been discussed for quite some time, but is just now coming to fruition. Traditionally, speech-recognition software has been constrained by hardware, but improved processors and increased memory capacities are starting to remove some of these limitations. With these barriers removed, companies that create software for the healthcare setting have the opportunity to write more successful applications. Among the criticisms of speech-recognition applications are the high rates of error and steep training curves. However, even in the face of such negative perceptions, there remains significant opportunities for speech recognition to allow healthcare providers and, more specifically, physicians, to work more efficiently and ultimately spend more time with their patients and less time completing necessary documentation. This article will identify opportunities for inclusion of speech-recognition technology in the healthcare setting and examine major categories of speech-recognition software--continuous speech recognition, command and control, and text-to-speech. We will discuss the advantages and disadvantages of each area, the limitations of the software today, and how future trends might affect them.

Hidden Markov models in automatic speech recognition

NASA Astrophysics Data System (ADS)

Wrzoskowicz, Adam

1993-11-01

This article describes a method for constructing an automatic speech recognition system based on hidden Markov models (HMMs). The author discusses the basic concepts of HMM theory and the application of these models to the analysis and recognition of speech signals. The author provides algorithms which make it possible to train the ASR system and recognize signals on the basis of distinct stochastic models of selected speech sound classes. The author describes the specific components of the system and the procedures used to model and recognize speech. The author discusses problems associated with the choice of optimal signal detection and parameterization characteristics and their effect on the performance of the system. The author presents different options for the choice of speech signal segments and their consequences for the ASR process. The author gives special attention to the use of lexical, syntactic, and semantic information for the purpose of improving the quality and efficiency of the system. The author also describes an ASR system developed by the Speech Acoustics Laboratory of the IBPT PAS. The author discusses the results of experiments on the effect of noise on the performance of the ASR system and describes methods of constructing HMM's designed to operate in a noisy environment. The author also describes a language for human-robot communications which was defined as a complex multilevel network from an HMM model of speech sounds geared towards Polish inflections. The author also added mandatory lexical and syntactic rules to the system for its communications vocabulary.

It doesn't matter what you say: FMRI correlates of voice learning and recognition independent of speech content.

PubMed

Zäske, Romi; Awwad Shiekh Hasan, Bashar; Belin, Pascal

2017-09-01

Listeners can recognize newly learned voices from previously unheard utterances, suggesting the acquisition of high-level speech-invariant voice representations during learning. Using functional magnetic resonance imaging (fMRI) we investigated the anatomical basis underlying the acquisition of voice representations for unfamiliar speakers independent of speech, and their subsequent recognition among novel voices. Specifically, listeners studied voices of unfamiliar speakers uttering short sentences and subsequently classified studied and novel voices as "old" or "new" in a recognition test. To investigate "pure" voice learning, i.e., independent of sentence meaning, we presented German sentence stimuli to non-German speaking listeners. To disentangle stimulus-invariant and stimulus-dependent learning, during the test phase we contrasted a "same sentence" condition in which listeners heard speakers repeating the sentences from the preceding study phase, with a "different sentence" condition. Voice recognition performance was above chance in both conditions although, as expected, performance was higher for same than for different sentences. During study phases activity in the left inferior frontal gyrus (IFG) was related to subsequent voice recognition performance and same versus different sentence condition, suggesting an involvement of the left IFG in the interactive processing of speaker and speech information during learning. Importantly, at test reduced activation for voices correctly classified as "old" compared to "new" emerged in a network of brain areas including temporal voice areas (TVAs) of the right posterior superior temporal gyrus (pSTG), as well as the right inferior/middle frontal gyrus (IFG/MFG), the right medial frontal gyrus, and the left caudate. This effect of voice novelty did not interact with sentence condition, suggesting a role of temporal voice-selective areas and extra-temporal areas in the explicit recognition of learned voice identity, independent of speech content. Copyright © 2017 Elsevier Ltd. All rights reserved.

Using speech recognition to enhance the Tongue Drive System functionality in computer access.

PubMed

Huo, Xueliang; Ghovanloo, Maysam

2011-01-01

Tongue Drive System (TDS) is a wireless tongue operated assistive technology (AT), which can enable people with severe physical disabilities to access computers and drive powered wheelchairs using their volitional tongue movements. TDS offers six discrete commands, simultaneously available to the users, for pointing and typing as a substitute for mouse and keyboard in computer access, respectively. To enhance the TDS performance in typing, we have added a microphone, an audio codec, and a wireless audio link to its readily available 3-axial magnetic sensor array, and combined it with a commercially available speech recognition software, the Dragon Naturally Speaking, which is regarded as one of the most efficient ways for text entry. Our preliminary evaluations indicate that the combined TDS and speech recognition technologies can provide end users with significantly higher performance than using each technology alone, particularly in completing tasks that require both pointing and text entry, such as web surfing.

Method and apparatus for obtaining complete speech signals for speech recognition applications

NASA Technical Reports Server (NTRS)

Abrash, Victor (Inventor); Cesari, Federico (Inventor); Franco, Horacio (Inventor); George, Christopher (Inventor); Zheng, Jing (Inventor)

2009-01-01

The present invention relates to a method and apparatus for obtaining complete speech signals for speech recognition applications. In one embodiment, the method continuously records an audio stream comprising a sequence of frames to a circular buffer. When a user command to commence or terminate speech recognition is received, the method obtains a number of frames of the audio stream occurring before or after the user command in order to identify an augmented audio signal for speech recognition processing. In further embodiments, the method analyzes the augmented audio signal in order to locate starting and ending speech endpoints that bound at least a portion of speech to be processed for recognition. At least one of the speech endpoints is located using a Hidden Markov Model.

Automatic Speech Recognition Predicts Speech Intelligibility and Comprehension for Listeners With Simulated Age-Related Hearing Loss.

PubMed

Fontan, Lionel; Ferrané, Isabelle; Farinas, Jérôme; Pinquier, Julien; Tardieu, Julien; Magnen, Cynthia; Gaillard, Pascal; Aumont, Xavier; Füllgrabe, Christian

2017-09-18

The purpose of this article is to assess speech processing for listeners with simulated age-related hearing loss (ARHL) and to investigate whether the observed performance can be replicated using an automatic speech recognition (ASR) system. The long-term goal of this research is to develop a system that will assist audiologists/hearing-aid dispensers in the fine-tuning of hearing aids. Sixty young participants with normal hearing listened to speech materials mimicking the perceptual consequences of ARHL at different levels of severity. Two intelligibility tests (repetition of words and sentences) and 1 comprehension test (responding to oral commands by moving virtual objects) were administered. Several language models were developed and used by the ASR system in order to fit human performances. Strong significant positive correlations were observed between human and ASR scores, with coefficients up to .99. However, the spectral smearing used to simulate losses in frequency selectivity caused larger declines in ASR performance than in human performance. Both intelligibility and comprehension scores for listeners with simulated ARHL are highly correlated with the performances of an ASR-based system. In the future, it needs to be determined if the ASR system is similarly successful in predicting speech processing in noise and by older people with ARHL.

Relating hearing loss and executive functions to hearing aid users' preference for, and speech recognition with, different combinations of binaural noise reduction and microphone directionality

PubMed Central

Neher, Tobias

2014-01-01

Knowledge of how executive functions relate to preferred hearing aid (HA) processing is sparse and seemingly inconsistent with related knowledge for speech recognition outcomes. This study thus aimed to find out if (1) performance on a measure of reading span (RS) is related to preferred binaural noise reduction (NR) strength, (2) similar relations exist for two different, non-verbal measures of executive function, (3) pure-tone average hearing loss (PTA), signal-to-noise ratio (SNR), and microphone directionality (DIR) also influence preferred NR strength, and (4) preference and speech recognition outcomes are similar. Sixty elderly HA users took part. Six HA conditions consisting of omnidirectional or cardioid microphones followed by inactive, moderate, or strong binaural NR as well as linear amplification were tested. Outcome was assessed at fixed SNRs using headphone simulations of a frontal target talker in a busy cafeteria. Analyses showed positive effects of active NR and DIR on preference, and negative and positive effects of, respectively, strong NR and DIR on speech recognition. Also, while moderate NR was the most preferred NR setting overall, preference for strong NR increased with SNR. No relation between RS and preference was found. However, larger PTA was related to weaker preference for inactive NR and stronger preference for strong NR for both microphone modes. Equivalent (but weaker) relations between worse performance on one non-verbal measure of executive function and the HA conditions without DIR were found. For speech recognition, there were relations between HA condition, PTA, and RS, but their pattern differed from that for preference. Altogether, these results indicate that, while moderate NR works well in general, a notable proportion of HA users prefer stronger NR. Furthermore, PTA and executive functions can account for some of the variability in preference for, and speech recognition with, different binaural NR and DIR settings. PMID:25538547

Age-related differences in listening effort during degraded speech recognition

PubMed Central

Ward, Kristina M.; Shen, Jing; Souza, Pamela E.; Grieco-Calub, Tina M.

2016-01-01

Objectives The purpose of the current study was to quantify age-related differences in executive control as it relates to dual-task performance, which is thought to represent listening effort, during degraded speech recognition. Design Twenty-five younger adults (18–24 years) and twenty-one older adults (56–82 years) completed a dual-task paradigm that consisted of a primary speech recognition task and a secondary visual monitoring task. Sentence material in the primary task was either unprocessed or spectrally degraded into 8, 6, or 4 spectral channels using noise-band vocoding. Performance on the visual monitoring task was assessed by the accuracy and reaction time of participants’ responses. Performance on the primary and secondary task was quantified in isolation (i.e., single task) and during the dual-task paradigm. Participants also completed a standardized psychometric measure of executive control, including attention and inhibition. Statistical analyses were implemented to evaluate changes in listeners’ performance on the primary and secondary tasks (1) per condition (unprocessed vs. vocoded conditions); (2) per task (baseline vs. dual task); and (3) per group (younger vs. older adults). Results Speech recognition declined with increasing spectral degradation for both younger and older adults when they performed the task in isolation or concurrently with the visual monitoring task. Older adults were slower and less accurate than younger adults on the visual monitoring task when performed in isolation, which paralleled age-related differences in standardized scores of executive control. When compared to single-task performance, older adults experienced greater declines in secondary-task accuracy, but not reaction time, than younger adults. Furthermore, results revealed that age-related differences in executive control significantly contributed to age-related differences on the visual monitoring task during the dual-task paradigm. Conclusions Older adults experienced significantly greater declines in secondary-task accuracy during degraded speech recognition than younger adults. These findings are interpreted as suggesting that older listeners expended greater listening effort than younger listeners, and may be partially attributed to age-related differences in executive control. PMID:27556526

Improving Mobile Phone Speech Recognition by Personalized Amplification: Application in People with Normal Hearing and Mild-to-Moderate Hearing Loss.

PubMed

Kam, Anna Chi Shan; Sung, John Ka Keung; Lee, Tan; Wong, Terence Ka Cheong; van Hasselt, Andrew

In this study, the authors evaluated the effect of personalized amplification on mobile phone speech recognition in people with and without hearing loss. This prospective study used double-blind, within-subjects, repeated measures, controlled trials to evaluate the effectiveness of applying personalized amplification based on the hearing level captured on the mobile device. The personalized amplification settings were created using modified one-third gain targets. The participants in this study included 100 adults of age between 20 and 78 years (60 with age-adjusted normal hearing and 40 with hearing loss). The performance of the participants with personalized amplification and standard settings was compared using both subjective and speech-perception measures. Speech recognition was measured in quiet and in noise using Cantonese disyllabic words. Subjective ratings on the quality, clarity, and comfortableness of the mobile signals were measured with an 11-point visual analog scale. Subjective preferences of the settings were also obtained by a paired-comparison procedure. The personalized amplification application provided better speech recognition via the mobile phone both in quiet and in noise for people with hearing impairment (improved 8 to 10%) and people with normal hearing (improved 1 to 4%). The improvement in speech recognition was significantly better for people with hearing impairment. When the average device output level was matched, more participants preferred to have the individualized gain than not to have it. The personalized amplification application has the potential to improve speech recognition for people with mild-to-moderate hearing loss, as well as people with normal hearing, in particular when listening in noisy environments.

Temporal Sensitivity Measured Shortly After Cochlear Implantation Predicts 6-Month Speech Recognition Outcome.

PubMed

Erb, Julia; Ludwig, Alexandra Annemarie; Kunke, Dunja; Fuchs, Michael; Obleser, Jonas

2018-04-24

Psychoacoustic tests assessed shortly after cochlear implantation are useful predictors of the rehabilitative speech outcome. While largely independent, both spectral and temporal resolution tests are important to provide an accurate prediction of speech recognition. However, rapid tests of temporal sensitivity are currently lacking. Here, we propose a simple amplitude modulation rate discrimination (AMRD) paradigm that is validated by predicting future speech recognition in adult cochlear implant (CI) patients. In 34 newly implanted patients, we used an adaptive AMRD paradigm, where broadband noise was modulated at the speech-relevant rate of ~4 Hz. In a longitudinal study, speech recognition in quiet was assessed using the closed-set Freiburger number test shortly after cochlear implantation (t0) as well as the open-set Freiburger monosyllabic word test 6 months later (t6). Both AMRD thresholds at t0 (r = -0.51) and speech recognition scores at t0 (r = 0.56) predicted speech recognition scores at t6. However, AMRD and speech recognition at t0 were uncorrelated, suggesting that those measures capture partially distinct perceptual abilities. A multiple regression model predicting 6-month speech recognition outcome with deafness duration and speech recognition at t0 improved from adjusted R = 0.30 to adjusted R = 0.44 when AMRD threshold was added as a predictor. These findings identify AMRD thresholds as a reliable, nonredundant predictor above and beyond established speech tests for CI outcome. This AMRD test could potentially be developed into a rapid clinical temporal-resolution test to be integrated into the postoperative test battery to improve the reliability of speech outcome prognosis.

Recognition and Localization of Speech by Adult Cochlear Implant Recipients Wearing a Digital Hearing Aid in the Nonimplanted Ear (Bimodal Hearing)

PubMed Central

Potts, Lisa G.; Skinner, Margaret W.; Litovsky, Ruth A.; Strube, Michael J; Kuk, Francis

2010-01-01

Background The use of bilateral amplification is now common clinical practice for hearing aid users but not for cochlear implant recipients. In the past, most cochlear implant recipients were implanted in one ear and wore only a monaural cochlear implant processor. There has been recent interest in benefits arising from bilateral stimulation that may be present for cochlear implant recipients. One option for bilateral stimulation is the use of a cochlear implant in one ear and a hearing aid in the opposite nonimplanted ear (bimodal hearing). Purpose This study evaluated the effect of wearing a cochlear implant in one ear and a digital hearing aid in the opposite ear on speech recognition and localization. Research Design A repeated-measures correlational study was completed. Study Sample Nineteen adult Cochlear Nucleus 24 implant recipients participated in the study. Intervention The participants were fit with a Widex Senso Vita 38 hearing aid to achieve maximum audibility and comfort within their dynamic range. Data Collection and Analysis Soundfield thresholds, loudness growth, speech recognition, localization, and subjective questionnaires were obtained six–eight weeks after the hearing aid fitting. Testing was completed in three conditions: hearing aid only, cochlear implant only, and cochlear implant and hearing aid (bimodal). All tests were repeated four weeks after the first test session. Repeated-measures analysis of variance was used to analyze the data. Significant effects were further examined using pairwise comparison of means or in the case of continuous moderators, regression analyses. The speech-recognition and localization tasks were unique, in that a speech stimulus presented from a variety of roaming azimuths (140 degree loudspeaker array) was used. Results Performance in the bimodal condition was significantly better for speech recognition and localization compared to the cochlear implant–only and hearing aid–only conditions. Performance was also different between these conditions when the location (i.e., side of the loudspeaker array that presented the word) was analyzed. In the bimodal condition, the speech-recognition and localization tasks were equal regardless of which side of the loudspeaker array presented the word, while performance was significantly poorer for the monaural conditions (hearing aid only and cochlear implant only) when the words were presented on the side with no stimulation. Binaural loudness summation of 1–3 dB was seen in soundfield thresholds and loudness growth in the bimodal condition. Measures of the audibility of sound with the hearing aid, including unaided thresholds, soundfield thresholds, and the Speech Intelligibility Index, were significant moderators of speech recognition and localization. Based on the questionnaire responses, participants showed a strong preference for bimodal stimulation. Conclusions These findings suggest that a well-fit digital hearing aid worn in conjunction with a cochlear implant is beneficial to speech recognition and localization. The dynamic test procedures used in this study illustrate the importance of bilateral hearing for locating, identifying, and switching attention between multiple speakers. It is recommended that unilateral cochlear implant recipients, with measurable unaided hearing thresholds, be fit with a hearing aid. PMID:19594084

Predicting word-recognition performance in noise by young listeners with normal hearing using acoustic, phonetic, and lexical variables.

PubMed

McArdle, Rachel; Wilson, Richard H

2008-06-01

To analyze the 50% correct recognition data that were from the Wilson et al (this issue) study and that were obtained from 24 listeners with normal hearing; also to examine whether acoustic, phonetic, or lexical variables can predict recognition performance for monosyllabic words presented in speech-spectrum noise. The specific variables are as follows: (a) acoustic variables (i.e., effective root-mean-square sound pressure level, duration), (b) phonetic variables (i.e., consonant features such as manner, place, and voicing for initial and final phonemes; vowel phonemes), and (c) lexical variables (i.e., word frequency, word familiarity, neighborhood density, neighborhood frequency). The descriptive, correlational study will examine the influence of acoustic, phonetic, and lexical variables on speech recognition in noise performance. Regression analysis demonstrated that 45% of the variance in the 50% point was accounted for by acoustic and phonetic variables whereas only 3% of the variance was accounted for by lexical variables. These findings suggest that monosyllabic word-recognition-in-noise is more dependent on bottom-up processing than on top-down processing. The results suggest that when speech-in-noise testing is used in a pre- and post-hearing-aid-fitting format, the use of monosyllabic words may be sensitive to changes in audibility resulting from amplification.

Particle Swarm Optimization Based Feature Enhancement and Feature Selection for Improved Emotion Recognition in Speech and Glottal Signals

PubMed Central

Muthusamy, Hariharan; Polat, Kemal; Yaacob, Sazali

2015-01-01

In the recent years, many research works have been published using speech related features for speech emotion recognition, however, recent studies show that there is a strong correlation between emotional states and glottal features. In this work, Mel-frequency cepstralcoefficients (MFCCs), linear predictive cepstral coefficients (LPCCs), perceptual linear predictive (PLP) features, gammatone filter outputs, timbral texture features, stationary wavelet transform based timbral texture features and relative wavelet packet energy and entropy features were extracted from the emotional speech (ES) signals and its glottal waveforms(GW). Particle swarm optimization based clustering (PSOC) and wrapper based particle swarm optimization (WPSO) were proposed to enhance the discerning ability of the features and to select the discriminating features respectively. Three different emotional speech databases were utilized to gauge the proposed method. Extreme learning machine (ELM) was employed to classify the different types of emotions. Different experiments were conducted and the results show that the proposed method significantly improves the speech emotion recognition performance compared to previous works published in the literature. PMID:25799141

Speech recognition: Acoustic-phonetic knowledge acquisition and representation

NASA Astrophysics Data System (ADS)

Zue, Victor W.

1988-09-01

The long-term research goal is to develop and implement speaker-independent continuous speech recognition systems. It is believed that the proper utilization of speech-specific knowledge is essential for such advanced systems. This research is thus directed toward the acquisition, quantification, and representation, of acoustic-phonetic and lexical knowledge, and the application of this knowledge to speech recognition algorithms. In addition, we are exploring new speech recognition alternatives based on artificial intelligence and connectionist techniques. We developed a statistical model for predicting the acoustic realization of stop consonants in various positions in the syllable template. A unification-based grammatical formalism was developed for incorporating this model into the lexical access algorithm. We provided an information-theoretic justification for the hierarchical structure of the syllable template. We analyzed segmented duration for vowels and fricatives in continuous speech. Based on contextual information, we developed durational models for vowels and fricatives that account for over 70 percent of the variance, using data from multiple, unknown speakers. We rigorously evaluated the ability of human spectrogram readers to identify stop consonants spoken by many talkers and in a variety of phonetic contexts. Incorporating the declarative knowledge used by the readers, we developed a knowledge-based system for stop identification. We achieved comparable system performance to that to the readers.

Potential Benefits of an Integrated Electric-Acoustic Sound Processor with Children: A Preliminary Report.

PubMed

Wolfe, Jace; Neumann, Sara; Schafer, Erin; Marsh, Megan; Wood, Mark; Baker, R Stanley

2017-02-01

A number of published studies have demonstrated the benefits of electric-acoustic stimulation (EAS) over conventional electric stimulation for adults with functional low-frequency acoustic hearing and severe-to-profound high-frequency hearing loss. These benefits potentially include better speech recognition in quiet and in noise, better localization, improvements in sound quality, better music appreciation and aptitude, and better pitch recognition. There is, however, a paucity of published reports describing the potential benefits and limitations of EAS for children with functional low-frequency acoustic hearing and severe-to-profound high-frequency hearing loss. The objective of this study was to explore the potential benefits of EAS for children. A repeated measures design was used to evaluate performance differences obtained with EAS stimulation versus acoustic- and electric-only stimulation. Seven users of Cochlear Nucleus Hybrid, Nucleus 24 Freedom, CI512, and CI422 implants were included in the study. Sentence recognition (assayed using the pediatric version of the AzBio sentence recognition test) was evaluated in quiet and at three fixed signal-to-noise ratios (SNR) (0, +5, and +10 dB). Functional hearing performance was also evaluated with the use of questionnaires, including the comparative version of the Speech, Spatial, and Qualities, the Listening Inventory for Education Revised, and the Children's Home Inventory for Listening Difficulties. Speech recognition in noise was typically better with EAS compared to participants' performance with acoustic- and electric-only stimulation, particularly when evaluated at the less favorable SNR. Additionally, in real-world situations, children generally preferred to use EAS compared to electric-only stimulation. Also, the participants' classroom teachers observed better hearing performance in the classroom with the use of EAS. Use of EAS provided better speech recognition in quiet and in noise when compared to performance obtained with use of acoustic- and electric-only stimulation, and children responded favorably to the use of EAS implemented in an integrated sound processor for real-world use. American Academy of Audiology

The Suitability of Cloud-Based Speech Recognition Engines for Language Learning

ERIC Educational Resources Information Center

Daniels, Paul; Iwago, Koji

2017-01-01

As online automatic speech recognition (ASR) engines become more accurate and more widely implemented with call software, it becomes important to evaluate the effectiveness and the accuracy of these recognition engines using authentic speech samples. This study investigates two of the most prominent cloud-based speech recognition engines--Apple's…

Individual differences in language and working memory affect children's speech recognition in noise.

PubMed

McCreery, Ryan W; Spratford, Meredith; Kirby, Benjamin; Brennan, Marc

2017-05-01

We examined how cognitive and linguistic skills affect speech recognition in noise for children with normal hearing. Children with better working memory and language abilities were expected to have better speech recognition in noise than peers with poorer skills in these domains. As part of a prospective, cross-sectional study, children with normal hearing completed speech recognition in noise for three types of stimuli: (1) monosyllabic words, (2) syntactically correct but semantically anomalous sentences and (3) semantically and syntactically anomalous word sequences. Measures of vocabulary, syntax and working memory were used to predict individual differences in speech recognition in noise. Ninety-six children with normal hearing, who were between 5 and 12 years of age. Higher working memory was associated with better speech recognition in noise for all three stimulus types. Higher vocabulary abilities were associated with better recognition in noise for sentences and word sequences, but not for words. Working memory and language both influence children's speech recognition in noise, but the relationships vary across types of stimuli. These findings suggest that clinical assessment of speech recognition is likely to reflect underlying cognitive and linguistic abilities, in addition to a child's auditory skills, consistent with the Ease of Language Understanding model.

Effects and modeling of phonetic and acoustic confusions in accented speech.

PubMed

Fung, Pascale; Liu, Yi

2005-11-01

Accented speech recognition is more challenging than standard speech recognition due to the effects of phonetic and acoustic confusions. Phonetic confusion in accented speech occurs when an expected phone is pronounced as a different one, which leads to erroneous recognition. Acoustic confusion occurs when the pronounced phone is found to lie acoustically between two baseform models and can be equally recognized as either one. We propose that it is necessary to analyze and model these confusions separately in order to improve accented speech recognition without degrading standard speech recognition. Since low phonetic confusion units in accented speech do not give rise to automatic speech recognition errors, we focus on analyzing and reducing phonetic and acoustic confusability under high phonetic confusion conditions. We propose using likelihood ratio test to measure phonetic confusion, and asymmetric acoustic distance to measure acoustic confusion. Only accent-specific phonetic units with low acoustic confusion are used in an augmented pronunciation dictionary, while phonetic units with high acoustic confusion are reconstructed using decision tree merging. Experimental results show that our approach is effective and superior to methods modeling phonetic confusion or acoustic confusion alone in accented speech, with a significant 5.7% absolute WER reduction, without degrading standard speech recognition.

Effect of high-frequency spectral components in computer recognition of dysarthric speech based on a Mel-cepstral stochastic model.

PubMed

Polur, Prasad D; Miller, Gerald E

2005-01-01

Computer speech recognition of individuals with dysarthria, such as cerebral palsy patients, requires a robust technique that can handle conditions of very high variability and limited training data. In this study, a hidden Markov model (HMM) was constructed and conditions investigated that would provide improved performance for a dysarthric speech (isolated word) recognition system intended to act as an assistive/control tool. In particular, we investigated the effect of high-frequency spectral components on the recognition rate of the system to determine if they contributed useful additional information to the system. A small-size vocabulary spoken by three cerebral palsy subjects was chosen. Mel-frequency cepstral coefficients extracted with the use of 15 ms frames served as training input to an ergodic HMM setup. Subsequent results demonstrated that no significant useful information was available to the system for enhancing its ability to discriminate dysarthric speech above 5.5 kHz in the current set of dysarthric data. The level of variability in input dysarthric speech patterns limits the reliability of the system. However, its application as a rehabilitation/control tool to assist dysarthric motor-impaired individuals such as cerebral palsy subjects holds sufficient promise.

The effect of sensorineural hearing loss and tinnitus on speech recognition over air and bone conduction military communications headsets.

PubMed

Manning, Candice; Mermagen, Timothy; Scharine, Angelique

2017-06-01

Military personnel are at risk for hearing loss due to noise exposure during deployment (USACHPPM, 2008). Despite mandated use of hearing protection, hearing loss and tinnitus are prevalent due to reluctance to use hearing protection. Bone conduction headsets can offer good speech intelligibility for normal hearing (NH) listeners while allowing the ears to remain open in quiet environments and the use of hearing protection when needed. Those who suffer from tinnitus, the experience of perceiving a sound not produced by an external source, often show degraded speech recognition; however, it is unclear whether this is a result of decreased hearing sensitivity or increased distractibility (Moon et al., 2015). It has been suggested that the vibratory stimulation of a bone conduction headset might ameliorate the effects of tinnitus on speech perception; however, there is currently no research to support or refute this claim (Hoare et al., 2014). Speech recognition of words presented over air conduction and bone conduction headsets was measured for three groups of listeners: NH, sensorineural hearing impaired, and/or tinnitus sufferers. Three levels of speech-to-noise (SNR = 0, -6, -12 dB) were created by embedding speech items in pink noise. Better speech recognition performance was observed with the bone conduction headset regardless of hearing profile, and speech intelligibility was a function of SNR. Discussion will include study limitations and the implications of these findings for those serving in the military. Published by Elsevier B.V.

Cochlear implant microphone location affects speech recognition in diffuse noise.

PubMed

Kolberg, Elizabeth R; Sheffield, Sterling W; Davis, Timothy J; Sunderhaus, Linsey W; Gifford, René H

2015-01-01

Despite improvements in cochlear implants (CIs), CI recipients continue to experience significant communicative difficulty in background noise. Many potential solutions have been proposed to help increase signal-to-noise ratio in noisy environments, including signal processing and external accessories. To date, however, the effect of microphone location on speech recognition in noise has focused primarily on hearing aid users. The purpose of this study was to (1) measure physical output for the T-Mic as compared with the integrated behind-the-ear (BTE) processor mic for various source azimuths, and (2) to investigate the effect of CI processor mic location for speech recognition in semi-diffuse noise with speech originating from various source azimuths as encountered in everyday communicative environments. A repeated-measures, within-participant design was used to compare performance across listening conditions. A total of 11 adults with Advanced Bionics CIs were recruited for this study. Physical acoustic output was measured on a Knowles Experimental Mannequin for Acoustic Research (KEMAR) for the T-Mic and BTE mic, with broadband noise presented at 0 and 90° (directed toward the implant processor). In addition to physical acoustic measurements, we also assessed recognition of sentences constructed by researchers at Texas Instruments, the Massachusetts Institute of Technology, and the Stanford Research Institute (TIMIT sentences) at 60 dBA for speech source azimuths of 0, 90, and 270°. Sentences were presented in a semi-diffuse restaurant noise originating from the R-SPACE 8-loudspeaker array. Signal-to-noise ratio was determined individually to achieve approximately 50% correct in the unilateral implanted listening condition with speech at 0°. Performance was compared across the T-Mic, 50/50, and the integrated BTE processor mic. The integrated BTE mic provided approximately 5 dB attenuation from 1500-4500 Hz for signals presented at 0° as compared with 90° (directed toward the processor). The T-Mic output was essentially equivalent for sources originating from 0 and 90°. Mic location also significantly affected sentence recognition as a function of source azimuth, with the T-Mic yielding the highest performance for speech originating from 0°. These results have clinical implications for (1) future implant processor design with respect to mic location, (2) mic settings for implant recipients, and (3) execution of advanced speech testing in the clinic. American Academy of Audiology.

Dichotic Word Recognition in Noise and the Right-Ear Advantage

ERIC Educational Resources Information Center

Roup, Christina M.

2011-01-01

Purpose: This study sought to compare dichotic right-ear advantages (REAs) of young adults to older adult data (C. M. Roup, T. L. Wiley, & R. H. Wilson, 2006) after matching for overall levels of recognition performance. Specifically, speech-spectrum noise was introduced in order to reduce dichotic recognition performance of young adults to a…

Towards fully analog hardware reservoir computing for speech recognition

NASA Astrophysics Data System (ADS)

Smerieri, Anteo; Duport, François; Paquot, Yvan; Haelterman, Marc; Schrauwen, Benjamin; Massar, Serge

2012-09-01

Reservoir computing is a very recent, neural network inspired unconventional computation technique, where a recurrent nonlinear system is used in conjunction with a linear readout to perform complex calculations, leveraging its inherent internal dynamics. In this paper we show the operation of an optoelectronic reservoir computer in which both the nonlinear recurrent part and the readout layer are implemented in hardware for a speech recognition application. The performance obtained is close to the one of to state-of-the-art digital reservoirs, while the analog architecture opens the way to ultrafast computation.

Analysis of Factors Affecting System Performance in the ASpIRE Challenge

DTIC Science & Technology

2015-12-13

performance in the ASpIRE (Automatic Speech recognition In Reverberant Environments) challenge. In particular, overall word error rate (WER) of the solver...systems is analyzed as a function of room, distance between talker and microphone, and microphone type. We also analyze speech activity detection...analysis will inform the design of future challenges and provide insight into the efficacy of current solutions addressing noisy reverberant speech

Melodic Contour Identification and Music Perception by Cochlear Implant Users

PubMed Central

Galvin, John J.; Fu, Qian-Jie; Shannon, Robert V.

2013-01-01

Research and outcomes with cochlear implants (CIs) have revealed a dichotomy in the cues necessary for speech and music recognition. CI devices typically transmit 16–22 spectral channels, each modulated slowly in time. This coarse representation provides enough information to support speech understanding in quiet and rhythmic perception in music, but not enough to support speech understanding in noise or melody recognition. Melody recognition requires some capacity for complex pitch perception, which in turn depends strongly on access to spectral fine structure cues. Thus, temporal envelope cues are adequate for speech perception under optimal listening conditions, while spectral fine structure cues are needed for music perception. In this paper, we present recent experiments that directly measure CI users’ melodic pitch perception using a melodic contour identification (MCI) task. While normal-hearing (NH) listeners’ performance was consistently high across experiments, MCI performance was highly variable across CI users. CI users’ MCI performance was significantly affected by instrument timbre, as well as by the presence of a competing instrument. In general, CI users had great difficulty extracting melodic pitch from complex stimuli. However, musically-experienced CI users often performed as well as NH listeners, and MCI training in less experienced subjects greatly improved performance. With fixed constraints on spectral resolution, such as it occurs with hearing loss or an auditory prosthesis, training and experience can provide a considerable improvements in music perception and appreciation. PMID:19673835

Age-related Effects on Word Recognition: Reliance on Cognitive Control Systems with Structural Declines in Speech-responsive Cortex

PubMed Central

Walczak, Adam; Ahlstrom, Jayne; Denslow, Stewart; Horwitz, Amy; Dubno, Judy R.

2008-01-01

Speech recognition can be difficult and effortful for older adults, even for those with normal hearing. Declining frontal lobe cognitive control has been hypothesized to cause age-related speech recognition problems. This study examined age-related changes in frontal lobe function for 15 clinically normal hearing adults (21–75 years) when they performed a word recognition task that was made challenging by decreasing word intelligibility. Although there were no age-related changes in word recognition, there were age-related changes in the degree of activity within left middle frontal gyrus (MFG) and anterior cingulate (ACC) regions during word recognition. Older adults engaged left MFG and ACC regions when words were most intelligible compared to younger adults who engaged these regions when words were least intelligible. Declining gray matter volume within temporal lobe regions responsive to word intelligibility significantly predicted left MFG activity, even after controlling for total gray matter volume, suggesting that declining structural integrity of brain regions responsive to speech leads to the recruitment of frontal regions when words are easily understood. Electronic supplementary material The online version of this article (doi:10.1007/s10162-008-0113-3) contains supplementary material, which is available to authorized users. PMID:18274825

Sequential Bilateral Cochlear Implantation in a Patient with Bilateral Meniere’s Disease

PubMed Central

Holden, Laura K.; Neely, J. Gail; Gotter, Brenda D.; Mispagel, Karen M.; Firszt, Jill B.

2012-01-01

This case study describes a 45 year old female with bilateral, profound sensorineural hearing loss due to Meniere’s disease. She received her first cochlear implant in the right ear in 2008 and the second cochlear implant in the left ear in 2010. The case study examines the enhancement to speech recognition, particularly in noise, provided by bilateral cochlear implants. Speech recognition tests were administered prior to obtaining the second implant and at a number of test intervals following activation of the second device. Speech recognition in quiet and noise as well as localization abilities were assessed in several conditions to determine bilateral benefit and performance differences between ears. The results of the speech recognition testing indicated a substantial improvement in the patient’s ability to understand speech in noise and her ability to localize sound when using bilateral cochlear implants compared to using a unilateral implant or an implant and a hearing aid. In addition, the patient reported considerable improvement in her ability to communicate in daily life when using bilateral implants versus a unilateral implant. This case suggests that cochlear implantation is a viable option for patients who have lost their hearing to Meniere’s disease even when a number of medical treatments and surgical interventions have been performed to control vertigo. In the case presented, bilateral cochlear implantation was necessary for this patient to communicate successfully at home and at work. PMID:22463939

Performance of Automated Speech Scoring on Different Low- to Medium-Entropy Item Types for Low-Proficiency English Learners. Research Report. ETS RR-17-12

ERIC Educational Resources Information Center

Loukina, Anastassia; Zechner, Klaus; Yoon, Su-Youn; Zhang, Mo; Tao, Jidong; Wang, Xinhao; Lee, Chong Min; Mulholland, Matthew

2017-01-01

This report presents an overview of the "SpeechRater"? automated scoring engine model building and evaluation process for several item types with a focus on a low-English-proficiency test-taker population. We discuss each stage of speech scoring, including automatic speech recognition, filtering models for nonscorable responses, and…

Auditory models for speech analysis

NASA Astrophysics Data System (ADS)

Maybury, Mark T.

This paper reviews the psychophysical basis for auditory models and discusses their application to automatic speech recognition. First an overview of the human auditory system is presented, followed by a review of current knowledge gleaned from neurological and psychoacoustic experimentation. Next, a general framework describes established peripheral auditory models which are based on well-understood properties of the peripheral auditory system. This is followed by a discussion of current enhancements to that models to include nonlinearities and synchrony information as well as other higher auditory functions. Finally, the initial performance of auditory models in the task of speech recognition is examined and additional applications are mentioned.

Examining explanations for fundamental frequency's contribution to speech intelligibility in noise

NASA Astrophysics Data System (ADS)

Schlauch, Robert S.; Miller, Sharon E.; Watson, Peter J.

2005-09-01

Laures and Weismer [JSLHR, 42, 1148 (1999)] reported that speech with natural variation in fundamental frequency (F0) is more intelligible in noise than speech with a flattened F0 contour. Cognitive-linguistic based explanations have been offered to account for this drop in intelligibility for the flattened condition, but a lower-level mechanism related to auditory streaming may be responsible. Numerous psychoacoustic studies have demonstrated that modulating a tone enables a listener to segregate it from background sounds. To test these rival hypotheses, speech recognition in noise was measured for sentences with six different F0 contours: unmodified, flattened at the mean, natural but exaggerated, reversed, and frequency modulated (rates of 2.5 and 5.0 Hz). The 180 stimulus sentences were produced by five talkers (30 sentences per condition). Speech recognition for fifteen listeners replicate earlier findings showing that flattening the F0 contour results in a roughly 10% reduction in recognition of key words compared with the natural condition. Although the exaggerated condition produced results comparable to those of the flattened condition, the other conditions with unnatural F0 contours all yielded significantly poorer performance than the flattened condition. These results support the cognitive, linguistic-based explanations for the reduction in performance.

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise.

PubMed

Shen, Jing; Souza, Pamela E

2017-09-18

This study investigated the effect of dynamic pitch in target speech on older and younger listeners' speech recognition in temporally modulated noise. First, we examined whether the benefit from dynamic-pitch cues depends on the temporal modulation of noise. Second, we tested whether older listeners can benefit from dynamic-pitch cues for speech recognition in noise. Last, we explored the individual factors that predict the amount of dynamic-pitch benefit for speech recognition in noise. Younger listeners with normal hearing and older listeners with varying levels of hearing sensitivity participated in the study, in which speech reception thresholds were measured with sentences in nonspeech noise. The younger listeners benefited more from dynamic pitch for speech recognition in temporally modulated noise than unmodulated noise. Older listeners were able to benefit from the dynamic-pitch cues but received less benefit from noise modulation than the younger listeners. For those older listeners with hearing loss, the amount of hearing loss strongly predicted the dynamic-pitch benefit for speech recognition in noise. Dynamic-pitch cues aid speech recognition in noise, particularly when noise has temporal modulation. Hearing loss negatively affects the dynamic-pitch benefit to older listeners with significant hearing loss.

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise

PubMed Central

Souza, Pamela E.

2017-01-01

Purpose This study investigated the effect of dynamic pitch in target speech on older and younger listeners' speech recognition in temporally modulated noise. First, we examined whether the benefit from dynamic-pitch cues depends on the temporal modulation of noise. Second, we tested whether older listeners can benefit from dynamic-pitch cues for speech recognition in noise. Last, we explored the individual factors that predict the amount of dynamic-pitch benefit for speech recognition in noise. Method Younger listeners with normal hearing and older listeners with varying levels of hearing sensitivity participated in the study, in which speech reception thresholds were measured with sentences in nonspeech noise. Results The younger listeners benefited more from dynamic pitch for speech recognition in temporally modulated noise than unmodulated noise. Older listeners were able to benefit from the dynamic-pitch cues but received less benefit from noise modulation than the younger listeners. For those older listeners with hearing loss, the amount of hearing loss strongly predicted the dynamic-pitch benefit for speech recognition in noise. Conclusions Dynamic-pitch cues aid speech recognition in noise, particularly when noise has temporal modulation. Hearing loss negatively affects the dynamic-pitch benefit to older listeners with significant hearing loss. PMID:28800370

[Creating language model of the forensic medicine domain for developing a autopsy recording system by automatic speech recognition].

PubMed

Niijima, H; Ito, N; Ogino, S; Takatori, T; Iwase, H; Kobayashi, M

2000-11-01

For the purpose of practical use of speech recognition technology for recording of forensic autopsy, a language model of the speech recording system, specialized for the forensic autopsy, was developed. The language model for the forensic autopsy by applying 3-gram model was created, and an acoustic model for Japanese speech recognition by Hidden Markov Model in addition to the above were utilized to customize the speech recognition engine for forensic autopsy. A forensic vocabulary set of over 10,000 words was compiled and some 300,000 sentence patterns were made to create the forensic language model, then properly mixing with a general language model to attain high exactitude. When tried by dictating autopsy findings, this speech recognition system was proved to be about 95% of recognition rate that seems to have reached to the practical usability in view of speech recognition software, though there remains rooms for improving its hardware and application-layer software.

The Relationship Between Spectral Modulation Detection and Speech Recognition: Adult Versus Pediatric Cochlear Implant Recipients

PubMed Central

Noble, Jack H.; Camarata, Stephen M.; Sunderhaus, Linsey W.; Dwyer, Robert T.; Dawant, Benoit M.; Dietrich, Mary S.; Labadie, Robert F.

2018-01-01

Adult cochlear implant (CI) recipients demonstrate a reliable relationship between spectral modulation detection and speech understanding. Prior studies documenting this relationship have focused on postlingually deafened adult CI recipients—leaving an open question regarding the relationship between spectral resolution and speech understanding for adults and children with prelingual onset of deafness. Here, we report CI performance on the measures of speech recognition and spectral modulation detection for 578 CI recipients including 477 postlingual adults, 65 prelingual adults, and 36 prelingual pediatric CI users. The results demonstrated a significant correlation between spectral modulation detection and various measures of speech understanding for 542 adult CI recipients. For 36 pediatric CI recipients, however, there was no significant correlation between spectral modulation detection and speech understanding in quiet or in noise nor was spectral modulation detection significantly correlated with listener age or age at implantation. These findings suggest that pediatric CI recipients might not depend upon spectral resolution for speech understanding in the same manner as adult CI recipients. It is possible that pediatric CI users are making use of different cues, such as those contained within the temporal envelope, to achieve high levels of speech understanding. Further investigation is warranted to investigate the relationship between spectral and temporal resolution and speech recognition to describe the underlying mechanisms driving peripheral auditory processing in pediatric CI users. PMID:29716437

Task-dependent modulation of the visual sensory thalamus assists visual-speech recognition.

PubMed

Díaz, Begoña; Blank, Helen; von Kriegstein, Katharina

2018-05-14

The cerebral cortex modulates early sensory processing via feed-back connections to sensory pathway nuclei. The functions of this top-down modulation for human behavior are poorly understood. Here, we show that top-down modulation of the visual sensory thalamus (the lateral geniculate body, LGN) is involved in visual-speech recognition. In two independent functional magnetic resonance imaging (fMRI) studies, LGN response increased when participants processed fast-varying features of articulatory movements required for visual-speech recognition, as compared to temporally more stable features required for face identification with the same stimulus material. The LGN response during the visual-speech task correlated positively with the visual-speech recognition scores across participants. In addition, the task-dependent modulation was present for speech movements and did not occur for control conditions involving non-speech biological movements. In face-to-face communication, visual speech recognition is used to enhance or even enable understanding what is said. Speech recognition is commonly explained in frameworks focusing on cerebral cortex areas. Our findings suggest that task-dependent modulation at subcortical sensory stages has an important role for communication: Together with similar findings in the auditory modality the findings imply that task-dependent modulation of the sensory thalami is a general mechanism to optimize speech recognition. Copyright © 2018. Published by Elsevier Inc.

Syntactic error modeling and scoring normalization in speech recognition: Error modeling and scoring normalization in the speech recognition task for adult literacy training

NASA Technical Reports Server (NTRS)

Olorenshaw, Lex; Trawick, David

1991-01-01

The purpose was to develop a speech recognition system to be able to detect speech which is pronounced incorrectly, given that the text of the spoken speech is known to the recognizer. Better mechanisms are provided for using speech recognition in a literacy tutor application. Using a combination of scoring normalization techniques and cheater-mode decoding, a reasonable acceptance/rejection threshold was provided. In continuous speech, the system was tested to be able to provide above 80 pct. correct acceptance of words, while correctly rejecting over 80 pct. of incorrectly pronounced words.

Bridging automatic speech recognition and psycholinguistics: Extending Shortlist to an end-to-end model of human speech recognition (L)

NASA Astrophysics Data System (ADS)

Scharenborg, Odette; ten Bosch, Louis; Boves, Lou; Norris, Dennis

2003-12-01

This letter evaluates potential benefits of combining human speech recognition (HSR) and automatic speech recognition by building a joint model of an automatic phone recognizer (APR) and a computational model of HSR, viz., Shortlist [Norris, Cognition 52, 189-234 (1994)]. Experiments based on ``real-life'' speech highlight critical limitations posed by some of the simplifying assumptions made in models of human speech recognition. These limitations could be overcome by avoiding hard phone decisions at the output side of the APR, and by using a match between the input and the internal lexicon that flexibly copes with deviations from canonical phonemic representations.

Contralateral Bimodal Stimulation: A Way to Enhance Speech Performance in Arabic-Speaking Cochlear Implant Patients.

PubMed

Abdeltawwab, Mohamed M; Khater, Ahmed; El-Anwar, Mohammad W

2016-01-01

The combination of acoustic and electric stimulation as a way to enhance speech recognition performance in cochlear implant (CI) users has generated considerable interest in the recent years. The purpose of this study was to evaluate the bimodal advantage of the FS4 speech processing strategy in combination with hearing aids (HA) as a means to improve low-frequency resolution in CI patients. Nineteen postlingual CI adults were selected to participate in this study. All patients wore implants on one side and HA on the contralateral side with residual hearing. Monosyllabic word recognition, speech in noise, and emotion and talker identification were assessed using CI with fine structure processing/FS4 and high-definition continuous interleaved sampling strategies, HA alone, and a combination of CI and HA. The bimodal stimulation showed improvement in speech performance and emotion identification for the question/statement/order tasks, which was statistically significant compared to patients with CI alone, but there were no significant statistical differences in intragender talker discrimination and emotion identification for the happy/angry/neutral tasks. The poorest performance was obtained with HA only, and it was statistically significant compared to the other modalities. The bimodal stimulation showed enhanced speech performance in CI patients, and it improves the limitations provided by electric or acoustic stimulation alone. © 2016 S. Karger AG, Basel.

Cingulo-opercular activity affects incidental memory encoding for speech in noise.

PubMed

Vaden, Kenneth I; Teubner-Rhodes, Susan; Ahlstrom, Jayne B; Dubno, Judy R; Eckert, Mark A

2017-08-15

Correctly understood speech in difficult listening conditions is often difficult to remember. A long-standing hypothesis for this observation is that the engagement of cognitive resources to aid speech understanding can limit resources available for memory encoding. This hypothesis is consistent with evidence that speech presented in difficult conditions typically elicits greater activity throughout cingulo-opercular regions of frontal cortex that are proposed to optimize task performance through adaptive control of behavior and tonic attention. However, successful memory encoding of items for delayed recognition memory tasks is consistently associated with increased cingulo-opercular activity when perceptual difficulty is minimized. The current study used a delayed recognition memory task to test competing predictions that memory encoding for words is enhanced or limited by the engagement of cingulo-opercular activity during challenging listening conditions. An fMRI experiment was conducted with twenty healthy adult participants who performed a word identification in noise task that was immediately followed by a delayed recognition memory task. Consistent with previous findings, word identification trials in the poorer signal-to-noise ratio condition were associated with increased cingulo-opercular activity and poorer recognition memory scores on average. However, cingulo-opercular activity decreased for correctly identified words in noise that were not recognized in the delayed memory test. These results suggest that memory encoding in difficult listening conditions is poorer when elevated cingulo-opercular activity is not sustained. Although increased attention to speech when presented in difficult conditions may detract from more active forms of memory maintenance (e.g., sub-vocal rehearsal), we conclude that task performance monitoring and/or elevated tonic attention supports incidental memory encoding in challenging listening conditions. Copyright © 2017 Elsevier Inc. All rights reserved.

Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms.

PubMed

Schädler, Marc R; Warzybok, Anna; Kollmeier, Birger

2018-01-01

The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid algorithm. FADE uses a simple automatic speech recognizer (ASR) to estimate the lowest achievable speech reception thresholds (SRTs) from simulated speech recognition experiments in an objective way, independent from any empirical reference data. Empirical data from the literature were used to evaluate the model in terms of predicted SRTs and benefits in SRT with the German matrix sentence recognition test when using eight single- and multichannel binaural noise-reduction algorithms. To allow individual predictions of SRTs in binaural conditions, the model was extended with a simple better ear approach and individualized by taking audiograms into account. In a realistic binaural cafeteria condition, FADE explained about 90% of the variance of the empirical SRTs for a group of normal-hearing listeners and predicted the corresponding benefits with a root-mean-square prediction error of 0.6 dB. This highlights the potential of the approach for the objective assessment of benefits in SRT without prior knowledge about the empirical data. The predictions for the group of listeners with impaired hearing explained 75% of the empirical variance, while the individual predictions explained less than 25%. Possibly, additional individual factors should be considered for more accurate predictions with impaired hearing. A competing talker condition clearly showed one limitation of current ASR technology, as the empirical performance with SRTs lower than -20 dB could not be predicted.

Objective Prediction of Hearing Aid Benefit Across Listener Groups Using Machine Learning: Speech Recognition Performance With Binaural Noise-Reduction Algorithms

PubMed Central

Schädler, Marc R.; Warzybok, Anna; Kollmeier, Birger

2018-01-01

The simulation framework for auditory discrimination experiments (FADE) was adopted and validated to predict the individual speech-in-noise recognition performance of listeners with normal and impaired hearing with and without a given hearing-aid algorithm. FADE uses a simple automatic speech recognizer (ASR) to estimate the lowest achievable speech reception thresholds (SRTs) from simulated speech recognition experiments in an objective way, independent from any empirical reference data. Empirical data from the literature were used to evaluate the model in terms of predicted SRTs and benefits in SRT with the German matrix sentence recognition test when using eight single- and multichannel binaural noise-reduction algorithms. To allow individual predictions of SRTs in binaural conditions, the model was extended with a simple better ear approach and individualized by taking audiograms into account. In a realistic binaural cafeteria condition, FADE explained about 90% of the variance of the empirical SRTs for a group of normal-hearing listeners and predicted the corresponding benefits with a root-mean-square prediction error of 0.6 dB. This highlights the potential of the approach for the objective assessment of benefits in SRT without prior knowledge about the empirical data. The predictions for the group of listeners with impaired hearing explained 75% of the empirical variance, while the individual predictions explained less than 25%. Possibly, additional individual factors should be considered for more accurate predictions with impaired hearing. A competing talker condition clearly showed one limitation of current ASR technology, as the empirical performance with SRTs lower than −20 dB could not be predicted. PMID:29692200

Development of a Mandarin-English Bilingual Speech Recognition System for Real World Music Retrieval

NASA Astrophysics Data System (ADS)

Zhang, Qingqing; Pan, Jielin; Lin, Yang; Shao, Jian; Yan, Yonghong

In recent decades, there has been a great deal of research into the problem of bilingual speech recognition-to develop a recognizer that can handle inter- and intra-sentential language switching between two languages. This paper presents our recent work on the development of a grammar-constrained, Mandarin-English bilingual Speech Recognition System (MESRS) for real world music retrieval. Two of the main difficult issues in handling the bilingual speech recognition systems for real world applications are tackled in this paper. One is to balance the performance and the complexity of the bilingual speech recognition system; the other is to effectively deal with the matrix language accents in embedded language**. In order to process the intra-sentential language switching and reduce the amount of data required to robustly estimate statistical models, a compact single set of bilingual acoustic models derived by phone set merging and clustering is developed instead of using two separate monolingual models for each language. In our study, a novel Two-pass phone clustering method based on Confusion Matrix (TCM) is presented and compared with the log-likelihood measure method. Experiments testify that TCM can achieve better performance. Since potential system users' native language is Mandarin which is regarded as a matrix language in our application, their pronunciations of English as the embedded language usually contain Mandarin accents. In order to deal with the matrix language accents in embedded language, different non-native adaptation approaches are investigated. Experiments show that model retraining method outperforms the other common adaptation methods such as Maximum A Posteriori (MAP). With the effective incorporation of approaches on phone clustering and non-native adaptation, the Phrase Error Rate (PER) of MESRS for English utterances was reduced by 24.47% relatively compared to the baseline monolingual English system while the PER on Mandarin utterances was comparable to that of the baseline monolingual Mandarin system. The performance for bilingual utterances achieved 22.37% relative PER reduction.

Exploring the Link Between Cognitive Abilities and Speech Recognition in the Elderly Under Different Listening Conditions

PubMed Central

Nuesse, Theresa; Steenken, Rike; Neher, Tobias; Holube, Inga

2018-01-01

Elderly listeners are known to differ considerably in their ability to understand speech in noise. Several studies have addressed the underlying factors that contribute to these differences. These factors include audibility, and age-related changes in supra-threshold auditory processing abilities, and it has been suggested that differences in cognitive abilities may also be important. The objective of this study was to investigate associations between performance in cognitive tasks and speech recognition under different listening conditions in older adults with either age appropriate hearing or hearing-impairment. To that end, speech recognition threshold (SRT) measurements were performed under several masking conditions that varied along the perceptual dimensions of dip listening, spatial separation, and informational masking. In addition, a neuropsychological test battery was administered, which included measures of verbal working and short-term memory, executive functioning, selective and divided attention, and lexical and semantic abilities. Age-matched groups of older adults with either age-appropriate hearing (ENH, n = 20) or aided hearing impairment (EHI, n = 21) participated. In repeated linear regression analyses, composite scores of cognitive test outcomes (evaluated using PCA) were included to predict SRTs. These associations were different for the two groups. When hearing thresholds were controlled for, composed cognitive factors were significantly associated with the SRTs for the ENH listeners. Whereas better lexical and semantic abilities were associated with lower (better) SRTs in this group, there was a negative association between attentional abilities and speech recognition in the presence of spatially separated speech-like maskers. For the EHI group, the pure-tone thresholds (averaged across 0.5, 1, 2, and 4 kHz) were significantly associated with the SRTs, despite the fact that all signals were amplified and therefore in principle audible. PMID:29867654

Tone classification of syllable-segmented Thai speech based on multilayer perception

NASA Astrophysics Data System (ADS)

Satravaha, Nuttavudh; Klinkhachorn, Powsiri; Lass, Norman

2002-05-01

Thai is a monosyllabic tonal language that uses tone to convey lexical information about the meaning of a syllable. Thus to completely recognize a spoken Thai syllable, a speech recognition system not only has to recognize a base syllable but also must correctly identify a tone. Hence, tone classification of Thai speech is an essential part of a Thai speech recognition system. Thai has five distinctive tones (``mid,'' ``low,'' ``falling,'' ``high,'' and ``rising'') and each tone is represented by a single fundamental frequency (F0) pattern. However, several factors, including tonal coarticulation, stress, intonation, and speaker variability, affect the F0 pattern of a syllable in continuous Thai speech. In this study, an efficient method for tone classification of syllable-segmented Thai speech, which incorporates the effects of tonal coarticulation, stress, and intonation, as well as a method to perform automatic syllable segmentation, were developed. Acoustic parameters were used as the main discriminating parameters. The F0 contour of a segmented syllable was normalized by using a z-score transformation before being presented to a tone classifier. The proposed system was evaluated on 920 test utterances spoken by 8 speakers. A recognition rate of 91.36% was achieved by the proposed system.

Lexical influences on competing speech perception in younger, middle-aged, and older adults

PubMed Central

Helfer, Karen S.; Jesse, Alexandra

2015-01-01

The influence of lexical characteristics of words in to-be-attended and to-be-ignored speech streams was examined in a competing speech task. Older, middle-aged, and younger adults heard pairs of low-cloze probability sentences in which the frequency or neighborhood density of words was manipulated in either the target speech stream or the masking speech stream. All participants also completed a battery of cognitive measures. As expected, for all groups, target words that occur frequently or that are from sparse lexical neighborhoods were easier to recognize than words that are infrequent or from dense neighborhoods. Compared to other groups, these neighborhood density effects were largest for older adults; the frequency effect was largest for middle-aged adults. Lexical characteristics of words in the to-be-ignored speech stream also affected recognition of to-be-attended words, but only when overall performance was relatively good (that is, when younger participants listened to the speech streams at a more advantageous signal-to-noise ratio). For these listeners, to-be-ignored masker words from sparse neighborhoods interfered with recognition of target speech more than masker words from dense neighborhoods. Amount of hearing loss and cognitive abilities relating to attentional control modulated overall performance as well as the strength of lexical influences. PMID:26233036

Using Speech Recognition to Enhance the Tongue Drive System Functionality in Computer Access

PubMed Central

Huo, Xueliang; Ghovanloo, Maysam

2013-01-01

Tongue Drive System (TDS) is a wireless tongue operated assistive technology (AT), which can enable people with severe physical disabilities to access computers and drive powered wheelchairs using their volitional tongue movements. TDS offers six discrete commands, simultaneously available to the users, for pointing and typing as a substitute for mouse and keyboard in computer access, respectively. To enhance the TDS performance in typing, we have added a microphone, an audio codec, and a wireless audio link to its readily available 3-axial magnetic sensor array, and combined it with a commercially available speech recognition software, the Dragon Naturally Speaking, which is regarded as one of the most efficient ways for text entry. Our preliminary evaluations indicate that the combined TDS and speech recognition technologies can provide end users with significantly higher performance than using each technology alone, particularly in completing tasks that require both pointing and text entry, such as web surfing. PMID:22255801

Voice emotion recognition by cochlear-implanted children and their normally-hearing peers

PubMed Central

Chatterjee, Monita; Zion, Danielle; Deroche, Mickael L.; Burianek, Brooke; Limb, Charles; Goren, Alison; Kulkarni, Aditya M.; Christensen, Julie A.

2014-01-01

Despite their remarkable success in bringing spoken language to hearing impaired listeners, the signal transmitted through cochlear implants (CIs) remains impoverished in spectro-temporal fine structure. As a consequence, pitch-dominant information such as voice emotion, is diminished. For young children, the ability to correctly identify the mood/intent of the speaker (which may not always be visible in their facial expression) is an important aspect of social and linguistic development. Previous work in the field has shown that children with cochlear implants (cCI) have significant deficits in voice emotion recognition relative to their normally hearing peers (cNH). Here, we report on voice emotion recognition by a cohort of 36 school-aged cCI. Additionally, we provide for the first time, a comparison of their performance to that of cNH and NH adults (aNH) listening to CI simulations of the same stimuli. We also provide comparisons to the performance of adult listeners with CIs (aCI), most of whom learned language primarily through normal acoustic hearing. Results indicate that, despite strong variability, on average, cCI perform similarly to their adult counterparts; that both groups’ mean performance is similar to aNHs’ performance with 8-channel noise-vocoded speech; that cNH achieve excellent scores in voice emotion recognition with full-spectrum speech, but on average, show significantly poorer scores than aNH with 8-channel noise-vocoded speech. A strong developmental effect was observed in the cNH with noise-vocoded speech in this task. These results point to the considerable benefit obtained by cochlear-implanted children from their devices, but also underscore the need for further research and development in this important and neglected area. PMID:25448167

Comparison of bimodal and bilateral cochlear implant users on speech recognition with competing talker, music perception, affective prosody discrimination, and talker identification.

PubMed

Cullington, Helen E; Zeng, Fan-Gang

2011-02-01

Despite excellent performance in speech recognition in quiet, most cochlear implant users have great difficulty with speech recognition in noise, music perception, identifying tone of voice, and discriminating different talkers. This may be partly due to the pitch coding in cochlear implant speech processing. Most current speech processing strategies use only the envelope information; the temporal fine structure is discarded. One way to improve electric pitch perception is to use residual acoustic hearing via a hearing aid on the nonimplanted ear (bimodal hearing). This study aimed to test the hypothesis that bimodal users would perform better than bilateral cochlear implant users on tasks requiring good pitch perception. Four pitch-related tasks were used. 1. Hearing in Noise Test (HINT) sentences spoken by a male talker with a competing female, male, or child talker. 2. Montreal Battery of Evaluation of Amusia. This is a music test with six subtests examining pitch, rhythm and timing perception, and musical memory. 3. Aprosodia Battery. This has five subtests evaluating aspects of affective prosody and recognition of sarcasm. 4. Talker identification using vowels spoken by 10 different talkers (three men, three women, two boys, and two girls). Bilateral cochlear implant users were chosen as the comparison group. Thirteen bimodal and 13 bilateral adult cochlear implant users were recruited; all had good speech perception in quiet. There were no significant differences between the mean scores of the bimodal and bilateral groups on any of the tests, although the bimodal group did perform better than the bilateral group on almost all tests. Performance on the different pitch-related tasks was not correlated, meaning that if a subject performed one task well they would not necessarily perform well on another. The correlation between the bimodal users' hearing threshold levels in the aided ear and their performance on these tasks was weak. Although the bimodal cochlear implant group performed better than the bilateral group on most parts of the four pitch-related tests, the differences were not statistically significant. The lack of correlation between test results shows that the tasks used are not simply providing a measure of pitch ability. Even if the bimodal users have better pitch perception, the real-world tasks used are reflecting more diverse skills than pitch. This research adds to the existing speech perception, language, and localization studies that show no significant difference between bimodal and bilateral cochlear implant users.

Post interaural neural net-based vowel recognition

NASA Astrophysics Data System (ADS)

Jouny, Ismail I.

2001-10-01

Interaural head related transfer functions are used to process speech signatures prior to neural net based recognition. Data representing the head related transfer function of a dummy has been collected at MIT and made available on the Internet. This data is used to pre-process vowel signatures to mimic the effects of human ear on speech perception. Signatures representing various vowels of the English language are then presented to a multi-layer perceptron trained using the back propagation algorithm for recognition purposes. The focus in this paper is to assess the effects of human interaural system on vowel recognition performance particularly when using a classification system that mimics the human brain such as a neural net.

A speech processing study using an acoustic model of a multiple-channel cochlear implant

NASA Astrophysics Data System (ADS)

Xu, Ying

1998-10-01

A cochlear implant is an electronic device designed to provide sound information for adults and children who have bilateral profound hearing loss. The task of representing speech signals as electrical stimuli is central to the design and performance of cochlear implants. Studies have shown that the current speech- processing strategies provide significant benefits to cochlear implant users. However, the evaluation and development of speech-processing strategies have been complicated by hardware limitations and large variability in user performance. To alleviate these problems, an acoustic model of a cochlear implant with the SPEAK strategy is implemented in this study, in which a set of acoustic stimuli whose psychophysical characteristics are as close as possible to those produced by a cochlear implant are presented on normal-hearing subjects. To test the effectiveness and feasibility of this acoustic model, a psychophysical experiment was conducted to match the performance of a normal-hearing listener using model- processed signals to that of a cochlear implant user. Good agreement was found between an implanted patient and an age-matched normal-hearing subject in a dynamic signal discrimination experiment, indicating that this acoustic model is a reasonably good approximation of a cochlear implant with the SPEAK strategy. The acoustic model was then used to examine the potential of the SPEAK strategy in terms of its temporal and frequency encoding of speech. It was hypothesized that better temporal and frequency encoding of speech can be accomplished by higher stimulation rates and a larger number of activated channels. Vowel and consonant recognition tests were conducted on normal-hearing subjects using speech tokens processed by the acoustic model, with different combinations of stimulation rate and number of activated channels. The results showed that vowel recognition was best at 600 pps and 8 activated channels, but further increases in stimulation rate and channel numbers were not beneficial. Manipulations of stimulation rate and number of activated channels did not appreciably affect consonant recognition. These results suggest that overall speech performance may improve by appropriately increasing stimulation rate and number of activated channels. Future revision of this acoustic model is necessary to provide more accurate amplitude representation of speech.

Speech intelligibility index predictions for young and old listeners in automobile noise: Can the index be improved by incorporating factors other than absolute threshold?

NASA Astrophysics Data System (ADS)

Saweikis, Meghan; Surprenant, Aimée M.; Davies, Patricia; Gallant, Don

2003-10-01

While young and old subjects with comparable audiograms tend to perform comparably on speech recognition tasks in quiet environments, the older subjects have more difficulty than the younger subjects with recognition tasks in degraded listening conditions. This suggests that factors other than an absolute threshold may account for some of the difficulty older listeners have on recognition tasks in noisy environments. Many metrics, including the Speech Intelligibility Index (SII), used to measure speech intelligibility, only consider an absolute threshold when accounting for age related hearing loss. Therefore these metrics tend to overestimate the performance for elderly listeners in noisy environments [Tobias et al., J. Acoust. Soc. Am. 83, 859-895 (1988)]. The present studies examine the predictive capabilities of the SII in an environment with automobile noise present. This is of interest because people's evaluation of the automobile interior sound is closely linked to their ability to carry on conversations with their fellow passengers. The four studies examine whether, for subjects with age related hearing loss, the accuracy of the SII can be improved by incorporating factors other than an absolute threshold into the model. [Work supported by Ford Motor Company.

A Hybrid Acoustic and Pronunciation Model Adaptation Approach for Non-native Speech Recognition

NASA Astrophysics Data System (ADS)

Oh, Yoo Rhee; Kim, Hong Kook

In this paper, we propose a hybrid model adaptation approach in which pronunciation and acoustic models are adapted by incorporating the pronunciation and acoustic variabilities of non-native speech in order to improve the performance of non-native automatic speech recognition (ASR). Specifically, the proposed hybrid model adaptation can be performed at either the state-tying or triphone-modeling level, depending at which acoustic model adaptation is performed. In both methods, we first analyze the pronunciation variant rules of non-native speakers and then classify each rule as either a pronunciation variant or an acoustic variant. The state-tying level hybrid method then adapts pronunciation models and acoustic models by accommodating the pronunciation variants in the pronunciation dictionary and by clustering the states of triphone acoustic models using the acoustic variants, respectively. On the other hand, the triphone-modeling level hybrid method initially adapts pronunciation models in the same way as in the state-tying level hybrid method; however, for the acoustic model adaptation, the triphone acoustic models are then re-estimated based on the adapted pronunciation models and the states of the re-estimated triphone acoustic models are clustered using the acoustic variants. From the Korean-spoken English speech recognition experiments, it is shown that ASR systems employing the state-tying and triphone-modeling level adaptation methods can relatively reduce the average word error rates (WERs) by 17.1% and 22.1% for non-native speech, respectively, when compared to a baseline ASR system.

Participation of the Classical Speech Areas in Auditory Long-Term Memory

PubMed Central

Karabanov, Anke Ninija; Paine, Rainer; Chao, Chi Chao; Schulze, Katrin; Scott, Brian; Hallett, Mark; Mishkin, Mortimer

2015-01-01

Accumulating evidence suggests that storing speech sounds requires transposing rapidly fluctuating sound waves into more easily encoded oromotor sequences. If so, then the classical speech areas in the caudalmost portion of the temporal gyrus (pSTG) and in the inferior frontal gyrus (IFG) may be critical for performing this acoustic-oromotor transposition. We tested this proposal by applying repetitive transcranial magnetic stimulation (rTMS) to each of these left-hemisphere loci, as well as to a nonspeech locus, while participants listened to pseudowords. After 5 minutes these stimuli were re-presented together with new ones in a recognition test. Compared to control-site stimulation, pSTG stimulation produced a highly significant increase in recognition error rate, without affecting reaction time. By contrast, IFG stimulation led only to a weak, non-significant, trend toward recognition memory impairment. Importantly, the impairment after pSTG stimulation was not due to interference with perception, since the same stimulation failed to affect pseudoword discrimination examined with short interstimulus intervals. Our findings suggest that pSTG is essential for transforming speech sounds into stored motor plans for reproducing the sound. Whether or not the IFG also plays a role in speech-sound recognition could not be determined from the present results. PMID:25815813

Participation of the classical speech areas in auditory long-term memory.

PubMed

Karabanov, Anke Ninija; Paine, Rainer; Chao, Chi Chao; Schulze, Katrin; Scott, Brian; Hallett, Mark; Mishkin, Mortimer

2015-01-01

Accumulating evidence suggests that storing speech sounds requires transposing rapidly fluctuating sound waves into more easily encoded oromotor sequences. If so, then the classical speech areas in the caudalmost portion of the temporal gyrus (pSTG) and in the inferior frontal gyrus (IFG) may be critical for performing this acoustic-oromotor transposition. We tested this proposal by applying repetitive transcranial magnetic stimulation (rTMS) to each of these left-hemisphere loci, as well as to a nonspeech locus, while participants listened to pseudowords. After 5 minutes these stimuli were re-presented together with new ones in a recognition test. Compared to control-site stimulation, pSTG stimulation produced a highly significant increase in recognition error rate, without affecting reaction time. By contrast, IFG stimulation led only to a weak, non-significant, trend toward recognition memory impairment. Importantly, the impairment after pSTG stimulation was not due to interference with perception, since the same stimulation failed to affect pseudoword discrimination examined with short interstimulus intervals. Our findings suggest that pSTG is essential for transforming speech sounds into stored motor plans for reproducing the sound. Whether or not the IFG also plays a role in speech-sound recognition could not be determined from the present results.

Minimal effects of visual memory training on the auditory performance of adult cochlear implant users

PubMed Central

Oba, Sandra I.; Galvin, John J.; Fu, Qian-Jie

2014-01-01

Auditory training has been shown to significantly improve cochlear implant (CI) users’ speech and music perception. However, it is unclear whether post-training gains in performance were due to improved auditory perception or to generally improved attention, memory and/or cognitive processing. In this study, speech and music perception, as well as auditory and visual memory were assessed in ten CI users before, during, and after training with a non-auditory task. A visual digit span (VDS) task was used for training, in which subjects recalled sequences of digits presented visually. After the VDS training, VDS performance significantly improved. However, there were no significant improvements for most auditory outcome measures (auditory digit span, phoneme recognition, sentence recognition in noise, digit recognition in noise), except for small (but significant) improvements in vocal emotion recognition and melodic contour identification. Post-training gains were much smaller with the non-auditory VDS training than observed in previous auditory training studies with CI users. The results suggest that post-training gains observed in previous studies were not solely attributable to improved attention or memory, and were more likely due to improved auditory perception. The results also suggest that CI users may require targeted auditory training to improve speech and music perception. PMID:23516087

Cochlear implant characteristics and speech perception skills of adolescents with long-term device use.

PubMed

Davidson, Lisa S; Geers, Ann E; Brenner, Christine

2010-10-01

Updated cochlear implant technology and optimized fitting can have a substantial impact on speech perception. The effects of upgrades in processor technology and aided thresholds on word recognition at soft input levels and sentence recognition in noise were examined. We hypothesized that updated speech processors and lower aided thresholds would allow improved recognition of soft speech without compromising performance in noise. 109 teenagers who had used a Nucleus 22-cochlear implant since preschool were tested with their current speech processor(s) (101 unilateral and 8 bilateral): 13 used the Spectra, 22 the ESPrit 22, 61 the ESPrit 3G, and 13 the Freedom. The Lexical Neighborhood Test (LNT) was administered at 70 and 50 dB SPL and the Bamford Kowal Bench sentences were administered in quiet and in noise. Aided thresholds were obtained for frequency-modulated tones from 250 to 4,000 Hz. Results were analyzed using repeated measures analysis of variance. Aided thresholds for the Freedom/3G group were significantly lower (better) than the Spectra/Sprint group. LNT scores at 50 dB were significantly higher for the Freedom/3G group. No significant differences between the 2 groups were found for the LNT at 70 or sentences in quiet or noise. Adolescents using updated processors that allowed for aided detection thresholds of 30 dB HL or better performed the best at soft levels. The BKB in noise results suggest that greater access to soft speech does not compromise listening in noise.

Speaker emotion recognition: from classical classifiers to deep neural networks

NASA Astrophysics Data System (ADS)

Mezghani, Eya; Charfeddine, Maha; Nicolas, Henri; Ben Amar, Chokri

2018-04-01

Speaker emotion recognition is considered among the most challenging tasks in recent years. In fact, automatic systems for security, medicine or education can be improved when considering the speech affective state. In this paper, a twofold approach for speech emotion classification is proposed. At the first side, a relevant set of features is adopted, and then at the second one, numerous supervised training techniques, involving classic methods as well as deep learning, are experimented. Experimental results indicate that deep architecture can improve classification performance on two affective databases, the Berlin Dataset of Emotional Speech and the SAVEE Dataset Surrey Audio-Visual Expressed Emotion.

Hybrid Speaker Recognition Using Universal Acoustic Model

NASA Astrophysics Data System (ADS)

Nishimura, Jun; Kuroda, Tadahiro

We propose a novel speaker recognition approach using a speaker-independent universal acoustic model (UAM) for sensornet applications. In sensornet applications such as “Business Microscope”, interactions among knowledge workers in an organization can be visualized by sensing face-to-face communication using wearable sensor nodes. In conventional studies, speakers are detected by comparing energy of input speech signals among the nodes. However, there are often synchronization errors among the nodes which degrade the speaker recognition performance. By focusing on property of the speaker's acoustic channel, UAM can provide robustness against the synchronization error. The overall speaker recognition accuracy is improved by combining UAM with the energy-based approach. For 0.1s speech inputs and 4 subjects, speaker recognition accuracy of 94% is achieved at the synchronization error less than 100ms.

HTM Spatial Pooler With Memristor Crossbar Circuits for Sparse Biometric Recognition.

PubMed

James, Alex Pappachen; Fedorova, Irina; Ibrayev, Timur; Kudithipudi, Dhireesha

2017-06-01

Hierarchical Temporal Memory (HTM) is an online machine learning algorithm that emulates the neo-cortex. The development of a scalable on-chip HTM architecture is an open research area. The two core substructures of HTM are spatial pooler and temporal memory. In this work, we propose a new Spatial Pooler circuit design with parallel memristive crossbar arrays for the 2D columns. The proposed design was validated on two different benchmark datasets, face recognition, and speech recognition. The circuits are simulated and analyzed using a practical memristor device model and 0.18 μm IBM CMOS technology model. The databases AR, YALE, ORL, and UFI, are used to test the performance of the design in face recognition. TIMIT dataset is used for the speech recognition.

Cochlear Implant Microphone Location Affects Speech Recognition in Diffuse Noise

PubMed Central

Kolberg, Elizabeth R.; Sheffield, Sterling W.; Davis, Timothy J.; Sunderhaus, Linsey W.; Gifford, René H.

2015-01-01

Background Despite improvements in cochlear implants (CIs), CI recipients continue to experience significant communicative difficulty in background noise. Many potential solutions have been proposed to help increase signal-to-noise ratio in noisy environments, including signal processing and external accessories. To date, however, the effect of microphone location on speech recognition in noise has focused primarily on hearing aid users. Purpose The purpose of this study was to (1) measure physical output for the T-Mic as compared with the integrated behind-the-ear(BTE) processor mic for various source azimuths, and (2) to investigate the effect of CI processor mic location for speech recognition in semi-diffuse noise with speech originating from various source azimuths as encountered in everyday communicative environments. Research Design A repeated-measures, within-participant design was used to compare performance across listening conditions. Study Sample A total of 11 adults with Advanced Bionics CIs were recruited for this study. Data Collection and Analysis Physical acoustic output was measured on a Knowles Experimental Mannequin for Acoustic Research (KEMAR) for the T-Mic and BTE mic, with broadband noise presented at 0 and 90° (directed toward the implant processor). In addition to physical acoustic measurements, we also assessed recognition of sentences constructed by researchers at Texas Instruments, the Massachusetts Institute of Technology, and the Stanford Research Institute (TIMIT sentences) at 60 dBA for speech source azimuths of 0, 90, and 270°. Sentences were presented in a semi-diffuse restaurant noise originating from the R-SPACE 8-loudspeaker array. Signal-to-noise ratio was determined individually to achieve approximately 50% correct in the unilateral implanted listening condition with speech at 0°. Performance was compared across the T-Mic, 50/50, and the integrated BTE processor mic. Results The integrated BTE mic provided approximately 5 dB attenuation from 1500–4500 Hz for signals presented at 0° as compared with 90° (directed toward the processor). The T-Mic output was essentially equivalent for sources originating from 0 and 90°. Mic location also significantly affected sentence recognition as a function of source azimuth, with the T-Mic yielding the highest performance for speech originating from 0°. Conclusions These results have clinical implications for (1) future implant processor design with respect to mic location, (2) mic settings for implant recipients, and (3) execution of advanced speech testing in the clinic. PMID:25597460

Strategies for Maximizing Speech-Recognition Performance: Adults with Mild to Moderately Severe Sensorineural Hearing Loss. EBP Briefs. Volume 11, Issue 4

ERIC Educational Resources Information Center

Donai, Jeremy J.; Schwartz, Jeremy C.

2016-01-01

Clinical Question: What high-frequency amplification strategy maximizes speechrecognition performance among adult hearing-impaired listeners with mild sloping to moderately severe sensorineural hearing loss? Method: Quick response review. Study Sources: EBSCO, PubMed, Google Scholar, as well as journals from the American Speech-Language-Hearing…

Multichannel Speech Enhancement Based on Generalized Gamma Prior Distribution with Its Online Adaptive Estimation

NASA Astrophysics Data System (ADS)

Dat, Tran Huy; Takeda, Kazuya; Itakura, Fumitada

We present a multichannel speech enhancement method based on MAP speech spectral magnitude estimation using a generalized gamma model of speech prior distribution, where the model parameters are adapted from actual noisy speech in a frame-by-frame manner. The utilization of a more general prior distribution with its online adaptive estimation is shown to be effective for speech spectral estimation in noisy environments. Furthermore, the multi-channel information in terms of cross-channel statistics are shown to be useful to better adapt the prior distribution parameters to the actual observation, resulting in better performance of speech enhancement algorithm. We tested the proposed algorithm in an in-car speech database and obtained significant improvements of the speech recognition performance, particularly under non-stationary noise conditions such as music, air-conditioner and open window.

Some Effects of Training on the Perception of Synthetic Speech

PubMed Central

Schwab, Eileen C.; Nusbaum, Howard C.; Pisoni, David B.

2012-01-01

The present study was conducted to determine the effects of training on the perception of synthetic speech. Three groups of subjects were tested with synthetic speech using the same tasks before and after training. One group was trained with synthetic speech. A second group went through the identical training procedures using natural speech. The third group received no training. Although performance of the three groups was the same prior to training, significant differences on the post-test measures of word recognition were observed: the group trained with synthetic speech performed much better than the other two groups. A six-month follow-up indicated that the group trained with synthetic speech displayed long-term retention of the knowledge and experience gained with prior exposure to synthetic speech generated by a text-to-speech system. PMID:2936671

Automatic concept extraction from spoken medical reports.

PubMed

Happe, André; Pouliquen, Bruno; Burgun, Anita; Cuggia, Marc; Le Beux, Pierre

2003-07-01

The objective of this project is to investigate methods whereby a combination of speech recognition and automated indexing methods substitute for current transcription and indexing practices. We based our study on existing speech recognition software programs and on NOMINDEX, a tool that extracts MeSH concepts from medical text in natural language and that is mainly based on a French medical lexicon and on the UMLS. For each document, the process consists of three steps: (1) dictation and digital audio recording, (2) speech recognition, (3) automatic indexing. The evaluation consisted of a comparison between the set of concepts extracted by NOMINDEX after the speech recognition phase and the set of keywords manually extracted from the initial document. The method was evaluated on a set of 28 patient discharge summaries extracted from the MENELAS corpus in French, corresponding to in-patients admitted for coronarography. The overall precision was 73% and the overall recall was 90%. Indexing errors were mainly due to word sense ambiguity and abbreviations. A specific issue was the fact that the standard French translation of MeSH terms lacks diacritics. A preliminary evaluation of speech recognition tools showed that the rate of accurate recognition was higher than 98%. Only 3% of the indexing errors were generated by inadequate speech recognition. We discuss several areas to focus on to improve this prototype. However, the very low rate of indexing errors due to speech recognition errors highlights the potential benefits of combining speech recognition techniques and automatic indexing.

Speech Recognition as a Transcription Aid: A Randomized Comparison With Standard Transcription

PubMed Central

Mohr, David N.; Turner, David W.; Pond, Gregory R.; Kamath, Joseph S.; De Vos, Cathy B.; Carpenter, Paul C.

2003-01-01

Objective. Speech recognition promises to reduce information entry costs for clinical information systems. It is most likely to be accepted across an organization if physicians can dictate without concerning themselves with real-time recognition and editing; assistants can then edit and process the computer-generated document. Our objective was to evaluate the use of speech-recognition technology in a randomized controlled trial using our institutional infrastructure. Design. Clinical note dictations from physicians in two specialty divisions were randomized to either a standard transcription process or a speech-recognition process. Secretaries and transcriptionists also were assigned randomly to each of these processes. Measurements. The duration of each dictation was measured. The amount of time spent processing a dictation to yield a finished document also was measured. Secretarial and transcriptionist productivity, defined as hours of secretary work per minute of dictation processed, was determined for speech recognition and standard transcription. Results. Secretaries in the endocrinology division were 87.3% (confidence interval, 83.3%, 92.3%) as productive with the speech-recognition technology as implemented in this study as they were using standard transcription. Psychiatry transcriptionists and secretaries were similarly less productive. Author, secretary, and type of clinical note were significant (p < 0.05) predictors of productivity. Conclusion. When implemented in an organization with an existing document-processing infrastructure (which included training and interfaces of the speech-recognition editor with the existing document entry application), speech recognition did not improve the productivity of secretaries or transcriptionists. PMID:12509359

Integrating the acoustics of running speech into the pure tone audiogram: a step from audibility to intelligibility and disability.

PubMed

Corthals, Paul

2008-01-01

The aim of the present study is to construct a simple method for visualizing and quantifying the audibility of speech on the audiogram and to predict speech intelligibility. The proposed method involves a series of indices on the audiogram form reflecting the sound pressure level distribution of running speech. The indices that coincide with a patient's pure tone thresholds reflect speech audibility and give evidence of residual functional hearing capacity. Two validation studies were conducted among sensorineurally hearing-impaired participants (n = 56 and n = 37, respectively) to investigate the relation with speech recognition ability and hearing disability. The potential of the new audibility indices as predictors for speech reception thresholds is comparable to the predictive potential of the ANSI 1968 articulation index and the ANSI 1997 speech intelligibility index. The sum of indices or a weighted combination can explain considerable proportions of variance in speech reception results for sentences in quiet free field conditions. The proportions of variance that can be explained in questionnaire results on hearing disability are less, presumably because the threshold indices almost exclusively reflect message audibility and much less the psychosocial consequences of hearing deficits. The outcomes underpin the validity of the new audibility indexing system, even though the proposed method may be better suited for predicting relative performance across a set of conditions than for predicting absolute speech recognition performance. (c) 2007 S. Karger AG, Basel

Robust Speech Processing & Recognition: Speaker ID, Language ID, Speech Recognition/Keyword Spotting, Diarization/Co-Channel/Environmental Characterization, Speaker State Assessment

DTIC Science & Technology

2015-10-01

Scoring, Gaussian Backend , etc.) as shown in Fig. 39. The methods in this domain also emphasized the ability to perform data purification for both...investigation using the same infrastructure was undertaken to explore Lombard effect “flavor” detection for improved speaker ID. The study The presence of...dimension selection and compared to a common N-gram frequency based selection. 2.1.2: Exploration on NN/DBN backend : Since Deep Neural Networks (DNN) have

Effect of Stimulation Rate on Cochlear Implant Users’ Phoneme, Word and Sentence Recognition in Quiet and in Noise

PubMed Central

Shannon, Robert V.; Cruz, Rachel J.; Galvin, John J.

2011-01-01

High stimulation rates in cochlear implants (CI) offer better temporal sampling, can induce stochastic-like firing of auditory neurons and can increase the electric dynamic range, all of which could improve CI speech performance. While commercial CI have employed increasingly high stimulation rates, no clear or consistent advantage has been shown for high rates. In this study, speech recognition was acutely measured with experimental processors in 7 CI subjects (Clarion CII users). The stimulation rate varied between (approx.) 600 and 4800 pulses per second per electrode (ppse) and the number of active electrodes varied between 4 and 16. Vowel, consonant, consonant-nucleus-consonant word and IEEE sentence recognition was acutely measured in quiet and in steady noise (+10 dB signal-to-noise ratio). Subjective quality ratings were obtained for each of the experimental processors in quiet and in noise. Except for a small difference for vowel recognition in quiet, there were no significant differences in performance among the experimental stimulation rates for any of the speech measures. There was also a small but significant increase in subjective quality rating as stimulation rates increased from 1200 to 2400 ppse in noise. Consistent with previous studies, performance significantly improved as the number of electrodes was increased from 4 to 8, but no significant difference showed between 8, 12 and 16 electrodes. Altogether, there was little-to-no advantage of high stimulation rates in quiet or in noise, at least for the present speech tests and conditions. PMID:20639631

A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition.

PubMed

Zhang, Yong; Li, Peng; Jin, Yingyezhe; Choe, Yoonsuck

2015-11-01

This paper presents a bioinspired digital liquid-state machine (LSM) for low-power very-large-scale-integration (VLSI)-based machine learning applications. To the best of the authors' knowledge, this is the first work that employs a bioinspired spike-based learning algorithm for the LSM. With the proposed online learning, the LSM extracts information from input patterns on the fly without needing intermediate data storage as required in offline learning methods such as ridge regression. The proposed learning rule is local such that each synaptic weight update is based only upon the firing activities of the corresponding presynaptic and postsynaptic neurons without incurring global communications across the neural network. Compared with the backpropagation-based learning, the locality of computation in the proposed approach lends itself to efficient parallel VLSI implementation. We use subsets of the TI46 speech corpus to benchmark the bioinspired digital LSM. To reduce the complexity of the spiking neural network model without performance degradation for speech recognition, we study the impacts of synaptic models on the fading memory of the reservoir and hence the network performance. Moreover, we examine the tradeoffs between synaptic weight resolution, reservoir size, and recognition performance and present techniques to further reduce the overhead of hardware implementation. Our simulation results show that in terms of isolated word recognition evaluated using the TI46 speech corpus, the proposed digital LSM rivals the state-of-the-art hidden Markov-model-based recognizer Sphinx-4 and outperforms all other reported recognizers including the ones that are based upon the LSM or neural networks.

Emotionally conditioning the target-speech voice enhances recognition of the target speech under "cocktail-party" listening conditions.

PubMed

Lu, Lingxi; Bao, Xiaohan; Chen, Jing; Qu, Tianshu; Wu, Xihong; Li, Liang

2018-05-01

Under a noisy "cocktail-party" listening condition with multiple people talking, listeners can use various perceptual/cognitive unmasking cues to improve recognition of the target speech against informational speech-on-speech masking. One potential unmasking cue is the emotion expressed in a speech voice, by means of certain acoustical features. However, it was unclear whether emotionally conditioning a target-speech voice that has none of the typical acoustical features of emotions (i.e., an emotionally neutral voice) can be used by listeners for enhancing target-speech recognition under speech-on-speech masking conditions. In this study we examined the recognition of target speech against a two-talker speech masker both before and after the emotionally neutral target voice was paired with a loud female screaming sound that has a marked negative emotional valence. The results showed that recognition of the target speech (especially the first keyword in a target sentence) was significantly improved by emotionally conditioning the target speaker's voice. Moreover, the emotional unmasking effect was independent of the unmasking effect of the perceived spatial separation between the target speech and the masker. Also, (skin conductance) electrodermal responses became stronger after emotional learning when the target speech and masker were perceptually co-located, suggesting an increase of listening efforts when the target speech was informationally masked. These results indicate that emotionally conditioning the target speaker's voice does not change the acoustical parameters of the target-speech stimuli, but the emotionally conditioned vocal features can be used as cues for unmasking target speech.

Deep Neural Networks for Speech Separation With Application to Robust Speech Recognition

DTIC Science & Technology

acoustic -phonetic features. The second objective is integration of spectrotemporal context for improved separation performance. Conditional random fields...will be used to encode contextual constraints. The third objective is to achieve robust ASR in the DNN framework through integrated acoustic modeling

Speech Processing and Recognition (SPaRe)

DTIC Science & Technology

2011-01-01

results in the areas of automatic speech recognition (ASR), speech processing, machine translation (MT), natural language processing ( NLP ), and...Processing ( NLP ), Information Retrieval (IR) 16. SECURITY CLASSIFICATION OF: UNCLASSIFED 17. LIMITATION OF ABSTRACT 18. NUMBER OF PAGES 19a. NAME...Figure 9, the IOC was only expected to provide document submission and search; automatic speech recognition (ASR) for English, Spanish, Arabic , and

Using Automatic Speech Recognition to Dictate Mathematical Expressions: The Development of the "TalkMaths" Application at Kingston University

ERIC Educational Resources Information Center

Wigmore, Angela; Hunter, Gordon; Pflugel, Eckhard; Denholm-Price, James; Binelli, Vincent

2009-01-01

Speech technology--especially automatic speech recognition--has now advanced to a level where it can be of great benefit both to able-bodied people and those with various disabilities. In this paper we describe an application "TalkMaths" which, using the output from a commonly-used conventional automatic speech recognition system,…

Severity-Based Adaptation with Limited Data for ASR to Aid Dysarthric Speakers

PubMed Central

Mustafa, Mumtaz Begum; Salim, Siti Salwah; Mohamed, Noraini; Al-Qatab, Bassam; Siong, Chng Eng

2014-01-01

Automatic speech recognition (ASR) is currently used in many assistive technologies, such as helping individuals with speech impairment in their communication ability. One challenge in ASR for speech-impaired individuals is the difficulty in obtaining a good speech database of impaired speakers for building an effective speech acoustic model. Because there are very few existing databases of impaired speech, which are also limited in size, the obvious solution to build a speech acoustic model of impaired speech is by employing adaptation techniques. However, issues that have not been addressed in existing studies in the area of adaptation for speech impairment are as follows: (1) identifying the most effective adaptation technique for impaired speech; and (2) the use of suitable source models to build an effective impaired-speech acoustic model. This research investigates the above-mentioned two issues on dysarthria, a type of speech impairment affecting millions of people. We applied both unimpaired and impaired speech as the source model with well-known adaptation techniques like the maximum likelihood linear regression (MLLR) and the constrained-MLLR(C-MLLR). The recognition accuracy of each impaired speech acoustic model is measured in terms of word error rate (WER), with further assessments, including phoneme insertion, substitution and deletion rates. Unimpaired speech when combined with limited high-quality speech-impaired data improves performance of ASR systems in recognising severely impaired dysarthric speech. The C-MLLR adaptation technique was also found to be better than MLLR in recognising mildly and moderately impaired speech based on the statistical analysis of the WER. It was found that phoneme substitution was the biggest contributing factor in WER in dysarthric speech for all levels of severity. The results show that the speech acoustic models derived from suitable adaptation techniques improve the performance of ASR systems in recognising impaired speech with limited adaptation data. PMID:24466004

Music and Speech Perception in Children Using Sung Speech

PubMed Central

Nie, Yingjiu; Galvin, John J.; Morikawa, Michael; André, Victoria; Wheeler, Harley; Fu, Qian-Jie

2018-01-01

This study examined music and speech perception in normal-hearing children with some or no musical training. Thirty children (mean age = 11.3 years), 15 with and 15 without formal music training participated in the study. Music perception was measured using a melodic contour identification (MCI) task; stimuli were a piano sample or sung speech with a fixed timbre (same word for each note) or a mixed timbre (different words for each note). Speech perception was measured in quiet and in steady noise using a matrix-styled sentence recognition task; stimuli were naturally intonated speech or sung speech with a fixed pitch (same note for each word) or a mixed pitch (different notes for each word). Significant musician advantages were observed for MCI and speech in noise but not for speech in quiet. MCI performance was significantly poorer with the mixed timbre stimuli. Speech performance in noise was significantly poorer with the fixed or mixed pitch stimuli than with spoken speech. Across all subjects, age at testing and MCI performance were significantly correlated with speech performance in noise. MCI and speech performance in quiet was significantly poorer for children than for adults from a related study using the same stimuli and tasks; speech performance in noise was significantly poorer for young than for older children. Long-term music training appeared to benefit melodic pitch perception and speech understanding in noise in these pediatric listeners. PMID:29609496

Music and Speech Perception in Children Using Sung Speech.

PubMed

Nie, Yingjiu; Galvin, John J; Morikawa, Michael; André, Victoria; Wheeler, Harley; Fu, Qian-Jie

2018-01-01

This study examined music and speech perception in normal-hearing children with some or no musical training. Thirty children (mean age = 11.3 years), 15 with and 15 without formal music training participated in the study. Music perception was measured using a melodic contour identification (MCI) task; stimuli were a piano sample or sung speech with a fixed timbre (same word for each note) or a mixed timbre (different words for each note). Speech perception was measured in quiet and in steady noise using a matrix-styled sentence recognition task; stimuli were naturally intonated speech or sung speech with a fixed pitch (same note for each word) or a mixed pitch (different notes for each word). Significant musician advantages were observed for MCI and speech in noise but not for speech in quiet. MCI performance was significantly poorer with the mixed timbre stimuli. Speech performance in noise was significantly poorer with the fixed or mixed pitch stimuli than with spoken speech. Across all subjects, age at testing and MCI performance were significantly correlated with speech performance in noise. MCI and speech performance in quiet was significantly poorer for children than for adults from a related study using the same stimuli and tasks; speech performance in noise was significantly poorer for young than for older children. Long-term music training appeared to benefit melodic pitch perception and speech understanding in noise in these pediatric listeners.

Cost-sensitive learning for emotion robust speaker recognition.

PubMed

Li, Dongdong; Yang, Yingchun; Dai, Weihui

2014-01-01

In the field of information security, voice is one of the most important parts in biometrics. Especially, with the development of voice communication through the Internet or telephone system, huge voice data resources are accessed. In speaker recognition, voiceprint can be applied as the unique password for the user to prove his/her identity. However, speech with various emotions can cause an unacceptably high error rate and aggravate the performance of speaker recognition system. This paper deals with this problem by introducing a cost-sensitive learning technology to reweight the probability of test affective utterances in the pitch envelop level, which can enhance the robustness in emotion-dependent speaker recognition effectively. Based on that technology, a new architecture of recognition system as well as its components is proposed in this paper. The experiment conducted on the Mandarin Affective Speech Corpus shows that an improvement of 8% identification rate over the traditional speaker recognition is achieved.

Cost-Sensitive Learning for Emotion Robust Speaker Recognition

PubMed Central

Li, Dongdong; Yang, Yingchun

2014-01-01

In the field of information security, voice is one of the most important parts in biometrics. Especially, with the development of voice communication through the Internet or telephone system, huge voice data resources are accessed. In speaker recognition, voiceprint can be applied as the unique password for the user to prove his/her identity. However, speech with various emotions can cause an unacceptably high error rate and aggravate the performance of speaker recognition system. This paper deals with this problem by introducing a cost-sensitive learning technology to reweight the probability of test affective utterances in the pitch envelop level, which can enhance the robustness in emotion-dependent speaker recognition effectively. Based on that technology, a new architecture of recognition system as well as its components is proposed in this paper. The experiment conducted on the Mandarin Affective Speech Corpus shows that an improvement of 8% identification rate over the traditional speaker recognition is achieved. PMID:24999492

The Downside of Greater Lexical Influences: Selectively Poorer Speech Perception in Noise

PubMed Central

Xie, Zilong; Tessmer, Rachel; Chandrasekaran, Bharath

2017-01-01

Purpose Although lexical information influences phoneme perception, the extent to which reliance on lexical information enhances speech processing in challenging listening environments is unclear. We examined the extent to which individual differences in lexical influences on phonemic processing impact speech processing in maskers containing varying degrees of linguistic information (2-talker babble or pink noise). Method Twenty-nine monolingual English speakers were instructed to ignore the lexical status of spoken syllables (e.g., gift vs. kift) and to only categorize the initial phonemes (/g/ vs. /k/). The same participants then performed speech recognition tasks in the presence of 2-talker babble or pink noise in audio-only and audiovisual conditions. Results Individuals who demonstrated greater lexical influences on phonemic processing experienced greater speech processing difficulties in 2-talker babble than in pink noise. These selective difficulties were present across audio-only and audiovisual conditions. Conclusion Individuals with greater reliance on lexical processes during speech perception exhibit impaired speech recognition in listening conditions in which competing talkers introduce audible linguistic interferences. Future studies should examine the locus of lexical influences/interferences on phonemic processing and speech-in-speech processing. PMID:28586824

The effects of reverberant self- and overlap-masking on speech recognition in cochlear implant listeners.

PubMed

Desmond, Jill M; Collins, Leslie M; Throckmorton, Chandra S

2014-06-01

Many cochlear implant (CI) listeners experience decreased speech recognition in reverberant environments [Kokkinakis et al., J. Acoust. Soc. Am. 129(5), 3221-3232 (2011)], which may be caused by a combination of self- and overlap-masking [Bolt and MacDonald, J. Acoust. Soc. Am. 21(6), 577-580 (1949)]. Determining the extent to which these effects decrease speech recognition for CI listeners may influence reverberation mitigation algorithms. This study compared speech recognition with ideal self-masking mitigation, with ideal overlap-masking mitigation, and with no mitigation. Under these conditions, mitigating either self- or overlap-masking resulted in significant improvements in speech recognition for both normal hearing subjects utilizing an acoustic model and for CI listeners using their own devices.

Children with a cochlear implant: characteristics and determinants of speech recognition, speech-recognition growth rate, and speech production.

PubMed

Wie, Ona Bø; Falkenberg, Eva-Signe; Tvete, Ole; Tomblin, Bruce

2007-05-01

The objectives of the study were to describe the characteristics of the first 79 prelingually deaf cochlear implant users in Norway and to investigate to what degree the variation in speech recognition, speech- recognition growth rate, and speech production could be explained by the characteristics of the child, the cochlear implant, the family, and the educational setting. Data gathered longitudinally were analysed using descriptive statistics, multiple regression, and growth-curve analysis. The results show that more than 50% of the variation could be explained by these characteristics. Daily user-time, non-verbal intelligence, mode of communication, length of CI experience, and educational placement had the highest effect on the outcome. The results also indicate that children educated in a bilingual approach to education have better speech perception and faster speech perception growth rate with increased focus on spoken language.

How does susceptibility to proactive interference relate to speech recognition in aided and unaided conditions?

PubMed

Ellis, Rachel J; Rönnberg, Jerker

2015-01-01

Proactive interference (PI) is the capacity to resist interference to the acquisition of new memories from information stored in the long-term memory. Previous research has shown that PI correlates significantly with the speech-in-noise recognition scores of younger adults with normal hearing. In this study, we report the results of an experiment designed to investigate the extent to which tests of visual PI relate to the speech-in-noise recognition scores of older adults with hearing loss, in aided and unaided conditions. The results suggest that measures of PI correlate significantly with speech-in-noise recognition only in the unaided condition. Furthermore the relation between PI and speech-in-noise recognition differs to that observed in younger listeners without hearing loss. The findings suggest that the relation between PI tests and the speech-in-noise recognition scores of older adults with hearing loss relates to capability of the test to index cognitive flexibility.

How does susceptibility to proactive interference relate to speech recognition in aided and unaided conditions?

PubMed Central

Ellis, Rachel J.; Rönnberg, Jerker

2015-01-01

Proactive interference (PI) is the capacity to resist interference to the acquisition of new memories from information stored in the long-term memory. Previous research has shown that PI correlates significantly with the speech-in-noise recognition scores of younger adults with normal hearing. In this study, we report the results of an experiment designed to investigate the extent to which tests of visual PI relate to the speech-in-noise recognition scores of older adults with hearing loss, in aided and unaided conditions. The results suggest that measures of PI correlate significantly with speech-in-noise recognition only in the unaided condition. Furthermore the relation between PI and speech-in-noise recognition differs to that observed in younger listeners without hearing loss. The findings suggest that the relation between PI tests and the speech-in-noise recognition scores of older adults with hearing loss relates to capability of the test to index cognitive flexibility. PMID:26283981

Computational validation of the motor contribution to speech perception.

PubMed

Badino, Leonardo; D'Ausilio, Alessandro; Fadiga, Luciano; Metta, Giorgio

2014-07-01

Action perception and recognition are core abilities fundamental for human social interaction. A parieto-frontal network (the mirror neuron system) matches visually presented biological motion information onto observers' motor representations. This process of matching the actions of others onto our own sensorimotor repertoire is thought to be important for action recognition, providing a non-mediated "motor perception" based on a bidirectional flow of information along the mirror parieto-frontal circuits. State-of-the-art machine learning strategies for hand action identification have shown better performances when sensorimotor data, as opposed to visual information only, are available during learning. As speech is a particular type of action (with acoustic targets), it is expected to activate a mirror neuron mechanism. Indeed, in speech perception, motor centers have been shown to be causally involved in the discrimination of speech sounds. In this paper, we review recent neurophysiological and machine learning-based studies showing (a) the specific contribution of the motor system to speech perception and (b) that automatic phone recognition is significantly improved when motor data are used during training of classifiers (as opposed to learning from purely auditory data). Copyright © 2014 Cognitive Science Society, Inc.

Multivariate predictors of music perception and appraisal by adult cochlear implant users.

PubMed

Gfeller, Kate; Oleson, Jacob; Knutson, John F; Breheny, Patrick; Driscoll, Virginia; Olszewski, Carol

2008-02-01

The research examined whether performance by adult cochlear implant recipients on a variety of recognition and appraisal tests derived from real-world music could be predicted from technological, demographic, and life experience variables, as well as speech recognition scores. A representative sample of 209 adults implanted between 1985 and 2006 participated. Using multiple linear regression models and generalized linear mixed models, sets of optimal predictor variables were selected that effectively predicted performance on a test battery that assessed different aspects of music listening. These analyses established the importance of distinguishing between the accuracy of music perception and the appraisal of musical stimuli when using music listening as an index of implant success. Importantly, neither device type nor processing strategy predicted music perception or music appraisal. Speech recognition performance was not a strong predictor of music perception, and primarily predicted music perception when the test stimuli included lyrics. Additionally, limitations in the utility of speech perception in predicting musical perception and appraisal underscore the utility of music perception as an alternative outcome measure for evaluating implant outcomes. Music listening background, residual hearing (i.e., hearing aid use), cognitive factors, and some demographic factors predicted several indices of perceptual accuracy or appraisal of music.

Accuracy of cochlear implant recipients in speech reception in the presence of background music.

PubMed

Gfeller, Kate; Turner, Christopher; Oleson, Jacob; Kliethermes, Stephanie; Driscoll, Virginia

2012-12-01

This study examined speech recognition abilities of cochlear implant (CI) recipients in the spectrally complex listening condition of 3 contrasting types of background music, and compared performance based upon listener groups: CI recipients using conventional long-electrode devices, Hybrid CI recipients (acoustic plus electric stimulation), and normal-hearing adults. We tested 154 long-electrode CI recipients using varied devices and strategies, 21 Hybrid CI recipients, and 49 normal-hearing adults on closed-set recognition of spondees presented in 3 contrasting forms of background music (piano solo, large symphony orchestra, vocal solo with small combo accompaniment) in an adaptive test. Signal-to-noise ratio thresholds for speech in music were examined in relation to measures of speech recognition in background noise and multitalker babble, pitch perception, and music experience. The signal-to-noise ratio thresholds for speech in music varied as a function of category of background music, group membership (long-electrode, Hybrid, normal-hearing), and age. The thresholds for speech in background music were significantly correlated with measures of pitch perception and thresholds for speech in background noise; auditory status was an important predictor. Evidence suggests that speech reception thresholds in background music change as a function of listener age (with more advanced age being detrimental), structural characteristics of different types of music, and hearing status (residual hearing). These findings have implications for everyday listening conditions such as communicating in social or commercial situations in which there is background music.

Automatic Speech Recognition from Neural Signals: A Focused Review.

PubMed

Herff, Christian; Schultz, Tanja

2016-01-01

Speech interfaces have become widely accepted and are nowadays integrated in various real-life applications and devices. They have become a part of our daily life. However, speech interfaces presume the ability to produce intelligible speech, which might be impossible due to either loud environments, bothering bystanders or incapabilities to produce speech (i.e., patients suffering from locked-in syndrome). For these reasons it would be highly desirable to not speak but to simply envision oneself to say words or sentences. Interfaces based on imagined speech would enable fast and natural communication without the need for audible speech and would give a voice to otherwise mute people. This focused review analyzes the potential of different brain imaging techniques to recognize speech from neural signals by applying Automatic Speech Recognition technology. We argue that modalities based on metabolic processes, such as functional Near Infrared Spectroscopy and functional Magnetic Resonance Imaging, are less suited for Automatic Speech Recognition from neural signals due to low temporal resolution but are very useful for the investigation of the underlying neural mechanisms involved in speech processes. In contrast, electrophysiologic activity is fast enough to capture speech processes and is therefor better suited for ASR. Our experimental results indicate the potential of these signals for speech recognition from neural data with a focus on invasively measured brain activity (electrocorticography). As a first example of Automatic Speech Recognition techniques used from neural signals, we discuss the Brain-to-text system.

Distributed Fusion in Sensor Networks with Information Genealogy

DTIC Science & Technology

2011-06-28

image processing [2], acoustic and speech recognition [3], multitarget tracking [4], distributed fusion [5], and Bayesian inference [6-7]. For...Adaptation for Distant-Talking Speech Recognition." in Proc Acoustics. Speech , and Signal Processing, 2004 |4| Y Bar-Shalom and T 1-. Fortmann...used in speech recognition and other classification applications [8]. But their use in underwater mine classification is limited. In this paper, we

Limited connected speech experiment

NASA Astrophysics Data System (ADS)

Landell, P. B.

1983-03-01

The purpose of this contract was to demonstrate that connected Speech Recognition (CSR) can be performed in real-time on a vocabulary of one hundred words and to test the performance of the CSR system for twenty-five male and twenty-five female speakers. This report describes the contractor's real-time laboratory CSR system, the data base and training software developed in accordance with the contract, and the results of the performance tests.

Neuroscience-inspired computational systems for speech recognition under noisy conditions

NASA Astrophysics Data System (ADS)

Schafer, Phillip B.

Humans routinely recognize speech in challenging acoustic environments with background music, engine sounds, competing talkers, and other acoustic noise. However, today's automatic speech recognition (ASR) systems perform poorly in such environments. In this dissertation, I present novel methods for ASR designed to approach human-level performance by emulating the brain's processing of sounds. I exploit recent advances in auditory neuroscience to compute neuron-based representations of speech, and design novel methods for decoding these representations to produce word transcriptions. I begin by considering speech representations modeled on the spectrotemporal receptive fields of auditory neurons. These representations can be tuned to optimize a variety of objective functions, which characterize the response properties of a neural population. I propose an objective function that explicitly optimizes the noise invariance of the neural responses, and find that it gives improved performance on an ASR task in noise compared to other objectives. The method as a whole, however, fails to significantly close the performance gap with humans. I next consider speech representations that make use of spiking model neurons. The neurons in this method are feature detectors that selectively respond to spectrotemporal patterns within short time windows in speech. I consider a number of methods for training the response properties of the neurons. In particular, I present a method using linear support vector machines (SVMs) and show that this method produces spikes that are robust to additive noise. I compute the spectrotemporal receptive fields of the neurons for comparison with previous physiological results. To decode the spike-based speech representations, I propose two methods designed to work on isolated word recordings. The first method uses a classical ASR technique based on the hidden Markov model. The second method is a novel template-based recognition scheme that takes advantage of the neural representation's invariance in noise. The scheme centers on a speech similarity measure based on the longest common subsequence between spike sequences. The combined encoding and decoding scheme outperforms a benchmark system in extremely noisy acoustic conditions. Finally, I consider methods for decoding spike representations of continuous speech. To help guide the alignment of templates to words, I design a syllable detection scheme that robustly marks the locations of syllabic nuclei. The scheme combines SVM-based training with a peak selection algorithm designed to improve noise tolerance. By incorporating syllable information into the ASR system, I obtain strong recognition results in noisy conditions, although the performance in noiseless conditions is below the state of the art. The work presented here constitutes a novel approach to the problem of ASR that can be applied in the many challenging acoustic environments in which we use computer technologies today. The proposed spike-based processing methods can potentially be exploited in effcient hardware implementations and could significantly reduce the computational costs of ASR. The work also provides a framework for understanding the advantages of spike-based acoustic coding in the human brain.

Unilateral Hearing Loss: Understanding Speech Recognition and Localization Variability-Implications for Cochlear Implant Candidacy.

PubMed

Firszt, Jill B; Reeder, Ruth M; Holden, Laura K

At a minimum, unilateral hearing loss (UHL) impairs sound localization ability and understanding speech in noisy environments, particularly if the loss is severe to profound. Accompanying the numerous negative consequences of UHL is considerable unexplained individual variability in the magnitude of its effects. Identification of covariables that affect outcome and contribute to variability in UHLs could augment counseling, treatment options, and rehabilitation. Cochlear implantation as a treatment for UHL is on the rise yet little is known about factors that could impact performance or whether there is a group at risk for poor cochlear implant outcomes when hearing is near-normal in one ear. The overall goal of our research is to investigate the range and source of variability in speech recognition in noise and localization among individuals with severe to profound UHL and thereby help determine factors relevant to decisions regarding cochlear implantation in this population. The present study evaluated adults with severe to profound UHL and adults with bilateral normal hearing. Measures included adaptive sentence understanding in diffuse restaurant noise, localization, roving-source speech recognition (words from 1 of 15 speakers in a 140° arc), and an adaptive speech-reception threshold psychoacoustic task with varied noise types and noise-source locations. There were three age-sex-matched groups: UHL (severe to profound hearing loss in one ear and normal hearing in the contralateral ear), normal hearing listening bilaterally, and normal hearing listening unilaterally. Although the normal-hearing-bilateral group scored significantly better and had less performance variability than UHLs on all measures, some UHL participants scored within the range of the normal-hearing-bilateral group on all measures. The normal-hearing participants listening unilaterally had better monosyllabic word understanding than UHLs for words presented on the blocked/deaf side but not the open/hearing side. In contrast, UHLs localized better than the normal-hearing unilateral listeners for stimuli on the open/hearing side but not the blocked/deaf side. This suggests that UHLs had learned strategies for improved localization on the side of the intact ear. The UHL and unilateral normal-hearing participant groups were not significantly different for speech in noise measures. UHL participants with childhood rather than recent hearing loss onset localized significantly better; however, these two groups did not differ for speech recognition in noise. Age at onset in UHL adults appears to affect localization ability differently than understanding speech in noise. Hearing thresholds were significantly correlated with speech recognition for UHL participants but not the other two groups. Auditory abilities of UHLs varied widely and could be explained only in part by hearing threshold levels. Age at onset and length of hearing loss influenced performance on some, but not all measures. Results support the need for a revised and diverse set of clinical measures, including sound localization, understanding speech in varied environments, and careful consideration of functional abilities as individuals with severe to profound UHL are being considered potential cochlear implant candidates.

Effective Prediction of Errors by Non-native Speakers Using Decision Tree for Speech Recognition-Based CALL System

NASA Astrophysics Data System (ADS)

Wang, Hongcui; Kawahara, Tatsuya

CALL (Computer Assisted Language Learning) systems using ASR (Automatic Speech Recognition) for second language learning have received increasing interest recently. However, it still remains a challenge to achieve high speech recognition performance, including accurate detection of erroneous utterances by non-native speakers. Conventionally, possible error patterns, based on linguistic knowledge, are added to the lexicon and language model, or the ASR grammar network. However, this approach easily falls in the trade-off of coverage of errors and the increase of perplexity. To solve the problem, we propose a method based on a decision tree to learn effective prediction of errors made by non-native speakers. An experimental evaluation with a number of foreign students learning Japanese shows that the proposed method can effectively generate an ASR grammar network, given a target sentence, to achieve both better coverage of errors and smaller perplexity, resulting in significant improvement in ASR accuracy.

Speech-perception training for older adults with hearing loss impacts word recognition and effort.

PubMed

Kuchinsky, Stefanie E; Ahlstrom, Jayne B; Cute, Stephanie L; Humes, Larry E; Dubno, Judy R; Eckert, Mark A

2014-10-01

The current pupillometry study examined the impact of speech-perception training on word recognition and cognitive effort in older adults with hearing loss. Trainees identified more words at the follow-up than at the baseline session. Training also resulted in an overall larger and faster peaking pupillary response, even when controlling for performance and reaction time. Perceptual and cognitive capacities affected the peak amplitude of the pupil response across participants but did not diminish the impact of training on the other pupil metrics. Thus, we demonstrated that pupillometry can be used to characterize training-related and individual differences in effort during a challenging listening task. Importantly, the results indicate that speech-perception training not only affects overall word recognition, but also a physiological metric of cognitive effort, which has the potential to be a biomarker of hearing loss intervention outcome. Copyright © 2014 Society for Psychophysiological Research.

Mispronunciation Detection for Language Learning and Speech Recognition Adaptation

ERIC Educational Resources Information Center

Ge, Zhenhao

2013-01-01

The areas of "mispronunciation detection" (or "accent detection" more specifically) within the speech recognition community are receiving increased attention now. Two application areas, namely language learning and speech recognition adaptation, are largely driving this research interest and are the focal points of this work.…

Longitudinal changes in speech recognition in older persons.

PubMed

Dubno, Judy R; Lee, Fu-Shing; Matthews, Lois J; Ahlstrom, Jayne B; Horwitz, Amy R; Mills, John H

2008-01-01

Recognition of isolated monosyllabic words in quiet and recognition of key words in low- and high-context sentences in babble were measured in a large sample of older persons enrolled in a longitudinal study of age-related hearing loss. Repeated measures were obtained yearly or every 2 to 3 years. To control for concurrent changes in pure-tone thresholds and speech levels, speech-recognition scores were adjusted using an importance-weighted speech-audibility metric (AI). Linear-regression slope estimated the rate of change in adjusted speech-recognition scores. Recognition of words in quiet declined significantly faster with age than predicted by declines in speech audibility. As subjects aged, observed scores deviated increasingly from AI-predicted scores, but this effect did not accelerate with age. Rate of decline in word recognition was significantly faster for females than males and for females with high serum progesterone levels, whereas noise history had no effect. Rate of decline did not accelerate with age but increased with degree of hearing loss, suggesting that with more severe injury to the auditory system, impairments to auditory function other than reduced audibility resulted in faster declines in word recognition as subjects aged. Recognition of key words in low- and high-context sentences in babble did not decline significantly with age.

Effects of Noise on Speech Recognition and Listening Effort in Children With Normal Hearing and Children With Mild Bilateral or Unilateral Hearing Loss.

PubMed

Lewis, Dawna; Schmid, Kendra; O'Leary, Samantha; Spalding, Jody; Heinrichs-Graham, Elizabeth; High, Robin

2016-10-01

This study examined the effects of stimulus type and hearing status on speech recognition and listening effort in children with normal hearing (NH) and children with mild bilateral hearing loss (MBHL) or unilateral hearing loss (UHL). Children (5-12 years of age) with NH (Experiment 1) and children (8-12 years of age) with MBHL, UHL, or NH (Experiment 2) performed consonant identification and word and sentence recognition in background noise. Percentage correct performance and verbal response time (VRT) were assessed (onset time, total duration). In general, speech recognition improved as signal-to-noise ratio (SNR) increased both for children with NH and children with MBHL or UHL. The groups did not differ on measures of VRT. Onset times were longer for incorrect than for correct responses. For correct responses only, there was a general increase in VRT with decreasing SNR. Findings indicate poorer sentence recognition in children with NH and MBHL or UHL as SNR decreases. VRT results suggest that greater effort was expended when processing stimuli that were incorrectly identified. Increasing VRT with decreasing SNR for correct responses also supports greater effort in poorer acoustic conditions. The absence of significant hearing status differences suggests that VRT was not differentially affected by MBHL, UHL, or NH for children in this study.

Non-native Listeners’ Recognition of High-Variability Speech Using PRESTO

PubMed Central

Tamati, Terrin N.; Pisoni, David B.

2015-01-01

Background Natural variability in speech is a significant challenge to robust successful spoken word recognition. In everyday listening environments, listeners must quickly adapt and adjust to multiple sources of variability in both the signal and listening environments. High-variability speech may be particularly difficult to understand for non-native listeners, who have less experience with the second language (L2) phonological system and less detailed knowledge of sociolinguistic variation of the L2. Purpose The purpose of this study was to investigate the effects of high-variability sentences on non-native speech recognition and to explore the underlying sources of individual differences in speech recognition abilities of non-native listeners. Research Design Participants completed two sentence recognition tasks involving high-variability and low-variability sentences. They also completed a battery of behavioral tasks and self-report questionnaires designed to assess their indexical processing skills, vocabulary knowledge, and several core neurocognitive abilities. Study Sample Native speakers of Mandarin (n = 25) living in the United States recruited from the Indiana University community participated in the current study. A native comparison group consisted of scores obtained from native speakers of English (n = 21) in the Indiana University community taken from an earlier study. Data Collection and Analysis Speech recognition in high-variability listening conditions was assessed with a sentence recognition task using sentences from PRESTO (Perceptually Robust English Sentence Test Open-Set) mixed in 6-talker multitalker babble. Speech recognition in low-variability listening conditions was assessed using sentences from HINT (Hearing In Noise Test) mixed in 6-talker multitalker babble. Indexical processing skills were measured using a talker discrimination task, a gender discrimination task, and a forced-choice regional dialect categorization task. Vocabulary knowledge was assessed with the WordFam word familiarity test, and executive functioning was assessed with the BRIEF-A (Behavioral Rating Inventory of Executive Function – Adult Version) self-report questionnaire. Scores from the non-native listeners on behavioral tasks and self-report questionnaires were compared with scores obtained from native listeners tested in a previous study and were examined for individual differences. Results Non-native keyword recognition scores were significantly lower on PRESTO sentences than on HINT sentences. Non-native listeners’ keyword recognition scores were also lower than native listeners’ scores on both sentence recognition tasks. Differences in performance on the sentence recognition tasks between non-native and native listeners were larger on PRESTO than on HINT, although group differences varied by signal-to-noise ratio. The non-native and native groups also differed in the ability to categorize talkers by region of origin and in vocabulary knowledge. Individual non-native word recognition accuracy on PRESTO sentences in multitalker babble at more favorable signal-to-noise ratios was found to be related to several BRIEF-A subscales and composite scores. However, non-native performance on PRESTO was not related to regional dialect categorization, talker and gender discrimination, or vocabulary knowledge. Conclusions High-variability sentences in multitalker babble were particularly challenging for non-native listeners. Difficulty under high-variability testing conditions was related to lack of experience with the L2, especially L2 sociolinguistic information, compared with native listeners. Individual differences among the non-native listeners were related to weaknesses in core neurocognitive abilities affecting behavioral control in everyday life. PMID:25405842

The cingulo-opercular network provides word-recognition benefit.

PubMed

Vaden, Kenneth I; Kuchinsky, Stefanie E; Cute, Stephanie L; Ahlstrom, Jayne B; Dubno, Judy R; Eckert, Mark A

2013-11-27

Recognizing speech in difficult listening conditions requires considerable focus of attention that is often demonstrated by elevated activity in putative attention systems, including the cingulo-opercular network. We tested the prediction that elevated cingulo-opercular activity provides word-recognition benefit on a subsequent trial. Eighteen healthy, normal-hearing adults (10 females; aged 20-38 years) performed word recognition (120 trials) in multi-talker babble at +3 and +10 dB signal-to-noise ratios during a sparse sampling functional magnetic resonance imaging (fMRI) experiment. Blood oxygen level-dependent (BOLD) contrast was elevated in the anterior cingulate cortex, anterior insula, and frontal operculum in response to poorer speech intelligibility and response errors. These brain regions exhibited significantly greater correlated activity during word recognition compared with rest, supporting the premise that word-recognition demands increased the coherence of cingulo-opercular network activity. Consistent with an adaptive control network explanation, general linear mixed model analyses demonstrated that increased magnitude and extent of cingulo-opercular network activity was significantly associated with correct word recognition on subsequent trials. These results indicate that elevated cingulo-opercular network activity is not simply a reflection of poor performance or error but also supports word recognition in difficult listening conditions.

Effects of input processing and type of personal frequency modulation system on speech-recognition performance of adults with cochlear implants.

PubMed

Wolfe, Jace; Schafer, Erin; Parkinson, Aaron; John, Andrew; Hudson, Mary; Wheeler, Julie; Mucci, Angie

2013-01-01

The objective of this study was to compare speech recognition in quiet and in noise for cochlear implant recipients using two different types of personal frequency modulation (FM) systems (directly coupled [direct auditory input] versus induction neckloop) with each of two sound processors (Cochlear Nucleus Freedom versus Cochlear Nucleus 5). Two different experiments were conducted within this study. In both these experiments, mixing of the FM signal within the Freedom processor was implemented via the same scheme used clinically for the Freedom sound processor. In Experiment 1, the aforementioned comparisons were conducted with the Nucleus 5 programmed so that the microphone and FM signals were mixed and then the mixed signals were subjected to autosensitivity control (ASC). In Experiment 2, comparisons between the two FM systems and processors were conducted again with the Nucleus 5 programmed to provide a more complex multistage implementation of ASC during the preprocessing stage. This study was a within-subject, repeated-measures design. Subjects were recruited from the patient population at the Hearts for Hearing Foundation in Oklahoma City, OK. Fifteen subjects participated in Experiment 1, and 16 subjects participated in Experiment 2. Subjects were adults who had used either unilateral or bilateral cochlear implants for at least 1 year. In this experiment, no differences were found in speech recognition in quiet obtained with the two different FM systems or the various sound-processor conditions. With each sound processor, speech recognition in noise was better with the directly coupled direct auditory input system relative to the neckloop system. The multistage ASC processing of the Nucleus 5 sound processor provided better performance than the single-stage approach for the Nucleus 5 and the Nucleus Freedom sound processor. Speech recognition in noise is substantially affected by the type of sound processor, FM system, and implementation of ASC used by a Cochlear implant recipient.

Speech feature discrimination in deaf children following cochlear implantation

NASA Astrophysics Data System (ADS)

Bergeson, Tonya R.; Pisoni, David B.; Kirk, Karen Iler

2002-05-01

Speech feature discrimination is a fundamental perceptual skill that is often assumed to underlie word recognition and sentence comprehension performance. To investigate the development of speech feature discrimination in deaf children with cochlear implants, we conducted a retrospective analysis of results from the Minimal Pairs Test (Robbins et al., 1988) selected from patients enrolled in a longitudinal study of speech perception and language development. The MP test uses a 2AFC procedure in which children hear a word and select one of two pictures (bat-pat). All 43 children were prelingually deafened, received a cochlear implant before 6 years of age or between ages 6 and 9, and used either oral or total communication. Children were tested once every 6 months to 1 year for 7 years; not all children were tested at each interval. By 2 years postimplant, the majority of these children achieved near-ceiling levels of discrimination performance for vowel height, vowel place, and consonant manner. Most of the children also achieved plateaus but did not reach ceiling performance for consonant place and voicing. The relationship between speech feature discrimination, spoken word recognition, and sentence comprehension will be discussed. [Work supported by NIH/NIDCD Research Grant No. R01DC00064 and NIH/NIDCD Training Grant No. T32DC00012.

Building Searchable Collections of Enterprise Speech Data.

ERIC Educational Resources Information Center

Cooper, James W.; Viswanathan, Mahesh; Byron, Donna; Chan, Margaret

The study has applied speech recognition and text-mining technologies to a set of recorded outbound marketing calls and analyzed the results. Since speaker-independent speech recognition technology results in a significantly lower recognition rate than that found when the recognizer is trained for a particular speaker, a number of post-processing…

Masked Speech Recognition and Reading Ability in School-Age Children: Is There a Relationship?

ERIC Educational Resources Information Center

Miller, Gabrielle; Lewis, Barbara; Benchek, Penelope; Buss, Emily; Calandruccio, Lauren

2018-01-01

Purpose: The relationship between reading (decoding) skills, phonological processing abilities, and masked speech recognition in typically developing children was explored. This experiment was designed to evaluate the relationship between phonological processing and decoding abilities and 2 aspects of masked speech recognition in typically…

Six characteristics of effective structured reporting and the inevitable integration with speech recognition.

PubMed

Liu, David; Zucherman, Mark; Tulloss, William B

2006-03-01

The reporting of radiological images is undergoing dramatic changes due to the introduction of two new technologies: structured reporting and speech recognition. Each technology has its own unique advantages. The highly organized content of structured reporting facilitates data mining and billing, whereas speech recognition offers a natural succession from the traditional dictation-transcription process. This article clarifies the distinction between the process and outcome of structured reporting, describes fundamental requirements for any effective structured reporting system, and describes the potential development of a novel, easy-to-use, customizable structured reporting system that incorporates speech recognition. This system should have all the advantages derived from structured reporting, accommodate a wide variety of user needs, and incorporate speech recognition as a natural component and extension of the overall reporting process.

Military applications of automatic speech recognition and future requirements

NASA Technical Reports Server (NTRS)

Beek, Bruno; Cupples, Edward J.

1977-01-01

An updated summary of the state-of-the-art of automatic speech recognition and its relevance to military applications is provided. A number of potential systems for military applications are under development. These include: (1) digital narrowband communication systems; (2) automatic speech verification; (3) on-line cartographic processing unit; (4) word recognition for militarized tactical data system; and (5) voice recognition and synthesis for aircraft cockpit.

Speech Recognition as a Support Service for Deaf and Hard of Hearing Students: Adaptation and Evaluation. Final Report to Spencer Foundation.

ERIC Educational Resources Information Center

Stinson, Michael; Elliot, Lisa; McKee, Barbara; Coyne, Gina

This report discusses a project that adapted new automatic speech recognition (ASR) technology to provide real-time speech-to-text transcription as a support service for students who are deaf and hard of hearing (D/HH). In this system, as the teacher speaks, a hearing intermediary, or captionist, dictates into the speech recognition system in a…

Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearinga)

PubMed Central

Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

2015-01-01

Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes. PMID:26233047

Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearing.

PubMed

Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

2015-07-01

Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes.

Text as a Supplement to Speech in Young and Older Adults a)

PubMed Central

Krull, Vidya; Humes, Larry E.

2015-01-01

Objective The purpose of this experiment was to quantify the contribution of visual text to auditory speech recognition in background noise. Specifically, we tested the hypothesis that partially accurate visual text from an automatic speech recognizer could be used successfully to supplement speech understanding in difficult listening conditions in older adults, with normal or impaired hearing. Our working hypotheses were based on what is known regarding audiovisual speech perception in the elderly from speechreading literature. We hypothesized that: 1) combining auditory and visual text information will result in improved recognition accuracy compared to auditory or visual text information alone; 2) benefit from supplementing speech with visual text (auditory and visual enhancement) in young adults will be greater than that in older adults; and 3) individual differences in performance on perceptual measures would be associated with cognitive abilities. Design Fifteen young adults with normal hearing, fifteen older adults with normal hearing, and fifteen older adults with hearing loss participated in this study. All participants completed sentence recognition tasks in auditory-only, text-only, and combined auditory-text conditions. The auditory sentence stimuli were spectrally shaped to restore audibility for the older participants with impaired hearing. All participants also completed various cognitive measures, including measures of working memory, processing speed, verbal comprehension, perceptual and cognitive speed, processing efficiency, inhibition, and the ability to form wholes from parts. Group effects were examined for each of the perceptual and cognitive measures. Audiovisual benefit was calculated relative to performance on auditory-only and visual-text only conditions. Finally, the relationship between perceptual measures and other independent measures were examined using principal-component factor analyses, followed by regression analyses. Results Both young and older adults performed similarly on nine out of ten perceptual measures (auditory, visual, and combined measures). Combining degraded speech with partially correct text from an automatic speech recognizer improved the understanding of speech in both young and older adults, relative to both auditory- and text-only performance. In all subjects, cognition emerged as a key predictor for a general speech-text integration ability. Conclusions These results suggest that neither age nor hearing loss affected the ability of subjects to benefit from text when used to support speech, after ensuring audibility through spectral shaping. These results also suggest that the benefit obtained by supplementing auditory input with partially accurate text is modulated by cognitive ability, specifically lexical and verbal skills. PMID:26458131

Some Neurocognitive Correlates of Noise-Vocoded Speech Perception in Children With Normal Hearing: A Replication and Extension of ).

PubMed

Roman, Adrienne S; Pisoni, David B; Kronenberger, William G; Faulkner, Kathleen F

Noise-vocoded speech is a valuable research tool for testing experimental hypotheses about the effects of spectral degradation on speech recognition in adults with normal hearing (NH). However, very little research has utilized noise-vocoded speech with children with NH. Earlier studies with children with NH focused primarily on the amount of spectral information needed for speech recognition without assessing the contribution of neurocognitive processes to speech perception and spoken word recognition. In this study, we first replicated the seminal findings reported by ) who investigated effects of lexical density and word frequency on noise-vocoded speech perception in a small group of children with NH. We then extended the research to investigate relations between noise-vocoded speech recognition abilities and five neurocognitive measures: auditory attention (AA) and response set, talker discrimination, and verbal and nonverbal short-term working memory. Thirty-one children with NH between 5 and 13 years of age were assessed on their ability to perceive lexically controlled words in isolation and in sentences that were noise-vocoded to four spectral channels. Children were also administered vocabulary assessments (Peabody Picture Vocabulary test-4th Edition and Expressive Vocabulary test-2nd Edition) and measures of AA (NEPSY AA and response set and a talker discrimination task) and short-term memory (visual digit and symbol spans). Consistent with the findings reported in the original ) study, we found that children perceived noise-vocoded lexically easy words better than lexically hard words. Words in sentences were also recognized better than the same words presented in isolation. No significant correlations were observed between noise-vocoded speech recognition scores and the Peabody Picture Vocabulary test-4th Edition using language quotients to control for age effects. However, children who scored higher on the Expressive Vocabulary test-2nd Edition recognized lexically easy words better than lexically hard words in sentences. Older children perceived noise-vocoded speech better than younger children. Finally, we found that measures of AA and short-term memory capacity were significantly correlated with a child's ability to perceive noise-vocoded isolated words and sentences. First, we successfully replicated the major findings from the ) study. Because familiarity, phonological distinctiveness and lexical competition affect word recognition, these findings provide additional support for the proposal that several foundational elementary neurocognitive processes underlie the perception of spectrally degraded speech. Second, we found strong and significant correlations between performance on neurocognitive measures and children's ability to recognize words and sentences noise-vocoded to four spectral channels. These findings extend earlier research suggesting that perception of spectrally degraded speech reflects early peripheral auditory processes, as well as additional contributions of executive function, specifically, selective attention and short-term memory processes in spoken word recognition. The present findings suggest that AA and short-term memory support robust spoken word recognition in children with NH even under compromised and challenging listening conditions. These results are relevant to research carried out with listeners who have hearing loss, because they are routinely required to encode, process, and understand spectrally degraded acoustic signals.

Some Neurocognitive Correlates of Noise-Vocoded Speech Perception in Children with Normal Hearing: A Replication and Extension of Eisenberg et al., 2002

PubMed Central

Roman, Adrienne S.; Pisoni, David B.; Kronenberger, William G.; Faulkner, Kathleen F.

2016-01-01

Objectives Noise-vocoded speech is a valuable research tool for testing experimental hypotheses about the effects of spectral-degradation on speech recognition in adults with normal hearing (NH). However, very little research has utilized noise-vocoded speech with children with NH. Earlier studies with children with NH focused primarily on the amount of spectral information needed for speech recognition without assessing the contribution of neurocognitive processes to speech perception and spoken word recognition. In this study, we first replicated the seminal findings reported by Eisenberg et al. (2002) who investigated effects of lexical density and word frequency on noise-vocoded speech perception in a small group of children with NH. We then extended the research to investigate relations between noise-vocoded speech recognition abilities and five neurocognitive measures: auditory attention and response set, talker discrimination and verbal and nonverbal short-term working memory. Design Thirty-one children with NH between 5 and 13 years of age were assessed on their ability to perceive lexically controlled words in isolation and in sentences that were noise-vocoded to four spectral channels. Children were also administered vocabulary assessments (PPVT-4 and EVT-2) and measures of auditory attention (NEPSY Auditory Attention (AA) and Response Set (RS) and a talker discrimination task (TD)) and short-term memory (visual digit and symbol spans). Results Consistent with the findings reported in the original Eisenberg et al. (2002) study, we found that children perceived noise-vocoded lexically easy words better than lexically hard words. Words in sentences were also recognized better than the same words presented in isolation. No significant correlations were observed between noise-vocoded speech recognition scores and the PPVT-4 using language quotients to control for age effects. However, children who scored higher on the EVT-2 recognized lexically easy words better than lexically hard words in sentences. Older children perceived noise-vocoded speech better than younger children. Finally, we found that measures of auditory attention and short-term memory capacity were significantly correlated with a child’s ability to perceive noise-vocoded isolated words and sentences. Conclusions First, we successfully replicated the major findings from the Eisenberg et al. (2002) study. Because familiarity, phonological distinctiveness and lexical competition affect word recognition, these findings provide additional support for the proposal that several foundational elementary neurocognitive processes underlie the perception of spectrally-degraded speech. Second, we found strong and significant correlations between performance on neurocognitive measures and children’s ability to recognize words and sentences noise-vocoded to four spectral channels. These findings extend earlier research suggesting that perception of spectrally-degraded speech reflects early peripheral auditory processes as well as additional contributions of executive function, specifically, selective attention and short-term memory processes in spoken word recognition. The present findings suggest that auditory attention and short-term memory support robust spoken word recognition in children with NH even under compromised and challenging listening conditions. These results are relevant to research carried out with listeners who have hearing loss, since they are routinely required to encode, process and understand spectrally-degraded acoustic signals. PMID:28045787

Strength Is in Numbers: Can Concordant Artificial Listeners Improve Prediction of Emotion from Speech?

PubMed

Martinelli, Eugenio; Mencattini, Arianna; Daprati, Elena; Di Natale, Corrado

2016-01-01

Humans can communicate their emotions by modulating facial expressions or the tone of their voice. Albeit numerous applications exist that enable machines to read facial emotions and recognize the content of verbal messages, methods for speech emotion recognition are still in their infancy. Yet, fast and reliable applications for emotion recognition are the obvious advancement of present 'intelligent personal assistants', and may have countless applications in diagnostics, rehabilitation and research. Taking inspiration from the dynamics of human group decision-making, we devised a novel speech emotion recognition system that applies, for the first time, a semi-supervised prediction model based on consensus. Three tests were carried out to compare this algorithm with traditional approaches. Labeling performances relative to a public database of spontaneous speeches are reported. The novel system appears to be fast, robust and less computationally demanding than traditional methods, allowing for easier implementation in portable voice-analyzers (as used in rehabilitation, research, industry, etc.) and for applications in the research domain (such as real-time pairing of stimuli to participants' emotional state, selective/differential data collection based on emotional content, etc.).

Sound Processing Features for Speaker-Dependent and Phrase-Independent Emotion Recognition in Berlin Database

NASA Astrophysics Data System (ADS)

Anagnostopoulos, Christos Nikolaos; Vovoli, Eftichia

An emotion recognition framework based on sound processing could improve services in human-computer interaction. Various quantitative speech features obtained from sound processing of acting speech were tested, as to whether they are sufficient or not to discriminate between seven emotions. Multilayered perceptrons were trained to classify gender and emotions on the basis of a 24-input vector, which provide information about the prosody of the speaker over the entire sentence using statistics of sound features. Several experiments were performed and the results were presented analytically. Emotion recognition was successful when speakers and utterances were “known” to the classifier. However, severe misclassifications occurred during the utterance-independent framework. At least, the proposed feature vector achieved promising results for utterance-independent recognition of high- and low-arousal emotions.

Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems

NASA Technical Reports Server (NTRS)

Huang, Yiteng; Chen, Jingdong; Chen, Shaoyan

2010-01-01

A voice-command human-machine interface system has been developed for spacesuit extravehicular activity (EVA) missions. A multichannel acoustic signal processing method has been created for distant speech acquisition in noisy and reverberant environments. This technology reduces noise by exploiting differences in the statistical nature of signal (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, the automatic speech recognition (ASR) accuracy can be improved to the level at which crewmembers would find the speech interface useful. The developed speech human/machine interface will enable both crewmember usability and operational efficiency. It can enjoy a fast rate of data/text entry, small overall size, and can be lightweight. In addition, this design will free the hands and eyes of a suited crewmember. The system components and steps include beam forming/multi-channel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, model adaption, ASR HMM (Hidden Markov Model) training, and ASR decoding. A state-of-the-art phoneme recognizer can obtain an accuracy rate of 65 percent when the training and testing data are free of noise. When it is used in spacesuits, the rate drops to about 33 percent. With the developed microphone array speech-processing technologies, the performance is improved and the phoneme recognition accuracy rate rises to 44 percent. The recognizer can be further improved by combining the microphone array and HMM model adaptation techniques and using speech samples collected from inside spacesuits. In addition, arithmetic complexity models for the major HMMbased ASR components were developed. They can help real-time ASR system designers select proper tasks when in the face of constraints in computational resources.

The influence of speech rate and accent on access and use of semantic information.

PubMed

Sajin, Stanislav M; Connine, Cynthia M

2017-04-01

Circumstances in which the speech input is presented in sub-optimal conditions generally lead to processing costs affecting spoken word recognition. The current study indicates that some processing demands imposed by listening to difficult speech can be mitigated by feedback from semantic knowledge. A set of lexical decision experiments examined how foreign accented speech and word duration impact access to semantic knowledge in spoken word recognition. Results indicate that when listeners process accented speech, the reliance on semantic information increases. Speech rate was not observed to influence semantic access, except in the setting in which unusually slow accented speech was presented. These findings support interactive activation models of spoken word recognition in which attention is modulated based on speech demands.

The Use of Lexical Neighborhood Test (LNT) in the Assessment of Speech Recognition Performance of Cochlear Implantees with Normal and Malformed Cochlea.

PubMed

Kant, Anjali R; Banik, Arun A

2017-09-01

The present study aims to use the model-based test Lexical Neighborhood Test (LNT), to assess speech recognition performance in early and late implanted hearing impaired children with normal and malformed cochlea. The LNT was administered to 46 children with congenital (prelingual) bilateral severe-profound sensorineural hearing loss, using Nucleus 24 cochlear implant. The children were grouped into Group 1-(early implantees with normal cochlea-EI); n = 15, 31/2-61/2 years of age; mean age at implantation-3½ years. Group 2-(late implantees with normal cochlea-LI); n = 15, 6-12 years of age; mean age at implantation-5 years. Group 3-(early implantees with malformed cochlea-EIMC); n = 9; 4.9-10.6 years of age; mean age at implantation-3.10 years. Group 4-(late implantees with malformed cochlea-LIMC); n = 7; 7-12.6 years of age; mean age at implantation-6.3 years. The following were the malformations: dysplastic cochlea, common cavity, Mondini's, incomplete partition-1 and 2 (IP-1 and 2), enlarged IAC. The children were instructed to repeat the words on hearing them. Means of the word and phoneme scores were computed. The LNT can also be used to assess speech recognition performance of hearing impaired children with malformed cochlea. When both easy and hard lists of LNT are considered, although, late implantees (with or without normal cochlea), have achieved higher word scores than early implantees, the differences are not statistically significant. Using LNT for assessing speech recognition enables a quantitative as well as descriptive report of phonological processes used by the children.

Spoken Word Recognition in Toddlers Who Use Cochlear Implants

PubMed Central

Grieco-Calub, Tina M.; Saffran, Jenny R.; Litovsky, Ruth Y.

2010-01-01

Purpose The purpose of this study was to assess the time course of spoken word recognition in 2-year-old children who use cochlear implants (CIs) in quiet and in the presence of speech competitors. Method Children who use CIs and age-matched peers with normal acoustic hearing listened to familiar auditory labels, in quiet or in the presence of speech competitors, while their eye movements to target objects were digitally recorded. Word recognition performance was quantified by measuring each child’s reaction time (i.e., the latency between the spoken auditory label and the first look at the target object) and accuracy (i.e., the amount of time that children looked at target objects within 367 ms to 2,000 ms after the label onset). Results Children with CIs were less accurate and took longer to fixate target objects than did age-matched children without hearing loss. Both groups of children showed reduced performance in the presence of the speech competitors, although many children continued to recognize labels at above-chance levels. Conclusion The results suggest that the unique auditory experience of young CI users slows the time course of spoken word recognition abilities. In addition, real-world listening environments may slow language processing in young language learners, regardless of their hearing status. PMID:19951921

Use of intonation contours for speech recognition in noise by cochlear implant recipients.

PubMed

Meister, Hartmut; Landwehr, Markus; Pyschny, Verena; Grugel, Linda; Walger, Martin

2011-05-01

The corruption of intonation contours has detrimental effects on sentence-based speech recognition in normal-hearing listeners Binns and Culling [(2007). J. Acoust. Soc. Am. 122, 1765-1776]. This paper examines whether this finding also applies to cochlear implant (CI) recipients. The subjects' F0-discrimination and speech perception in the presence of noise were measured, using sentences with regular and inverted F0-contours. The results revealed that speech recognition for regular contours was significantly better than for inverted contours. This difference was related to the subjects' F0-discrimination providing further evidence that the perception of intonation patterns is important for the CI-mediated speech recognition in noise.

The effects of speech controls on performance in advanced helicopters in a double stimulation paradigm

NASA Technical Reports Server (NTRS)

Bortolussi, Michael R.; Vidulich, Michael A.

1991-01-01

The potential benefit of speech as a control modality has been investigated with mixed results. Earlier studies suggests that speech controls can reduce the potential of manual control overloads and improve time-sharing performance. However, these benefits were not without costs. Pilots reported higher workload levels associated with the use of speech controls. To further investigate these previous findings, an experiment was conducted in a simulation of an advanced single-pilot, scout/attack helicopter at NASA-Ames' ICAB (interchangeable cab) facility. Objective performance data suggested that speech control modality was effective in reducing interference of discrete, time-shared responses during continuous flight control activity. Subjective ratings, however, indicated that the speech control modality increased workload. Post-flight debriefing indicated that these results were mainly due to the increased effort to speak precisely to a less than perfect voice recognition system.

Speech recognition features for EEG signal description in detection of neonatal seizures.

PubMed

Temko, A; Boylan, G; Marnane, W; Lightbody, G

2010-01-01

In this work, features which are usually employed in automatic speech recognition (ASR) are used for the detection of neonatal seizures in newborn EEG. Three conventional ASR feature sets are compared to the feature set which has been previously developed for this task. The results indicate that the thoroughly-studied spectral envelope based ASR features perform reasonably well on their own. Additionally, the SVM Recursive Feature Elimination routine is applied to all extracted features pooled together. It is shown that ASR features consistently appear among the top-rank features.

Voice emotion recognition by cochlear-implanted children and their normally-hearing peers.

PubMed

Chatterjee, Monita; Zion, Danielle J; Deroche, Mickael L; Burianek, Brooke A; Limb, Charles J; Goren, Alison P; Kulkarni, Aditya M; Christensen, Julie A

2015-04-01

Despite their remarkable success in bringing spoken language to hearing impaired listeners, the signal transmitted through cochlear implants (CIs) remains impoverished in spectro-temporal fine structure. As a consequence, pitch-dominant information such as voice emotion, is diminished. For young children, the ability to correctly identify the mood/intent of the speaker (which may not always be visible in their facial expression) is an important aspect of social and linguistic development. Previous work in the field has shown that children with cochlear implants (cCI) have significant deficits in voice emotion recognition relative to their normally hearing peers (cNH). Here, we report on voice emotion recognition by a cohort of 36 school-aged cCI. Additionally, we provide for the first time, a comparison of their performance to that of cNH and NH adults (aNH) listening to CI simulations of the same stimuli. We also provide comparisons to the performance of adult listeners with CIs (aCI), most of whom learned language primarily through normal acoustic hearing. Results indicate that, despite strong variability, on average, cCI perform similarly to their adult counterparts; that both groups' mean performance is similar to aNHs' performance with 8-channel noise-vocoded speech; that cNH achieve excellent scores in voice emotion recognition with full-spectrum speech, but on average, show significantly poorer scores than aNH with 8-channel noise-vocoded speech. A strong developmental effect was observed in the cNH with noise-vocoded speech in this task. These results point to the considerable benefit obtained by cochlear-implanted children from their devices, but also underscore the need for further research and development in this important and neglected area. This article is part of a Special Issue entitled . Copyright © 2014 Elsevier B.V. All rights reserved.

Speech processing using maximum likelihood continuity mapping

DOEpatents

Hogden, John E.

2000-01-01

Speech processing is obtained that, given a probabilistic mapping between static speech sounds and pseudo-articulator positions, allows sequences of speech sounds to be mapped to smooth sequences of pseudo-articulator positions. In addition, a method for learning a probabilistic mapping between static speech sounds and pseudo-articulator position is described. The method for learning the mapping between static speech sounds and pseudo-articulator position uses a set of training data composed only of speech sounds. The said speech processing can be applied to various speech analysis tasks, including speech recognition, speaker recognition, speech coding, speech synthesis, and voice mimicry.

Speech processing using maximum likelihood continuity mapping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogden, J.E.

Speech processing is obtained that, given a probabilistic mapping between static speech sounds and pseudo-articulator positions, allows sequences of speech sounds to be mapped to smooth sequences of pseudo-articulator positions. In addition, a method for learning a probabilistic mapping between static speech sounds and pseudo-articulator position is described. The method for learning the mapping between static speech sounds and pseudo-articulator position uses a set of training data composed only of speech sounds. The said speech processing can be applied to various speech analysis tasks, including speech recognition, speaker recognition, speech coding, speech synthesis, and voice mimicry.

Supporting Dictation Speech Recognition Error Correction: The Impact of External Information

ERIC Educational Resources Information Center

Shi, Yongmei; Zhou, Lina

2011-01-01

Although speech recognition technology has made remarkable progress, its wide adoption is still restricted by notable effort made and frustration experienced by users while correcting speech recognition errors. One of the promising ways to improve error correction is by providing user support. Although support mechanisms have been proposed for…

Application of an auditory model to speech recognition.

PubMed

Cohen, J R

1989-06-01

Some aspects of auditory processing are incorporated in a front end for the IBM speech-recognition system [F. Jelinek, "Continuous speech recognition by statistical methods," Proc. IEEE 64 (4), 532-556 (1976)]. This new process includes adaptation, loudness scaling, and mel warping. Tests show that the design is an improvement over previous algorithms.

Rate and onset cues can improve cochlear implant synthetic vowel recognition in noise

PubMed Central

Mc Laughlin, Myles; Reilly, Richard B.; Zeng, Fan-Gang

2013-01-01

Understanding speech-in-noise is difficult for most cochlear implant (CI) users. Speech-in-noise segregation cues are well understood for acoustic hearing but not for electric hearing. This study investigated the effects of stimulation rate and onset delay on synthetic vowel-in-noise recognition in CI subjects. In experiment I, synthetic vowels were presented at 50, 145, or 795 pulse/s and noise at the same three rates, yielding nine combinations. Recognition improved significantly if the noise had a lower rate than the vowel, suggesting that listeners can use temporal gaps in the noise to detect a synthetic vowel. This hypothesis is supported by accurate prediction of synthetic vowel recognition using a temporal integration window model. Using lower rates a similar trend was observed in normal hearing subjects. Experiment II found that for CI subjects, a vowel onset delay improved performance if the noise had a lower or higher rate than the synthetic vowel. These results show that differing rates or onset times can improve synthetic vowel-in-noise recognition, indicating a need to develop speech processing strategies that encode or emphasize these cues. PMID:23464025

Speech recognition training for enhancing written language generation by a traumatic brain injury survivor.

PubMed

Manasse, N J; Hux, K; Rankin-Erickson, J L

2000-11-01

Impairments in motor functioning, language processing, and cognitive status may impact the written language performance of traumatic brain injury (TBI) survivors. One strategy to minimize the impact of these impairments is to use a speech recognition system. The purpose of this study was to explore the effect of mild dysarthria and mild cognitive-communication deficits secondary to TBI on a 19-year-old survivor's mastery and use of such a system-specifically, Dragon Naturally Speaking. Data included the % of the participant's words accurately perceived by the system over time, the participant's accuracy over time in using commands for navigation and error correction, and quantitative and qualitative changes in the participant's written texts generated with and without the use of the speech recognition system. Results showed that Dragon NaturallySpeaking was approximately 80% accurate in perceiving words spoken by the participant, and the participant quickly and easily mastered all navigation and error correction commands presented. Quantitatively, the participant produced a greater amount of text using traditional word processing and a standard keyboard than using the speech recognition system. Minimal qualitative differences appeared between writing samples. Discussion of factors that may have contributed to the obtained results and that may affect the generalization of the findings to other TBI survivors is provided.

The influence of audibility on speech recognition with nonlinear frequency compression for children and adults with hearing loss

PubMed Central

McCreery, Ryan W.; Alexander, Joshua; Brennan, Marc A.; Hoover, Brenda; Kopun, Judy; Stelmachowicz, Patricia G.

2014-01-01

Objective The primary goal of nonlinear frequency compression (NFC) and other frequency lowering strategies is to increase the audibility of high-frequency sounds that are not otherwise audible with conventional hearing-aid processing due to the degree of hearing loss, limited hearing aid bandwidth or a combination of both factors. The aim of the current study was to compare estimates of speech audibility processed by NFC to improvements in speech recognition for a group of children and adults with high-frequency hearing loss. Design Monosyllabic word recognition was measured in noise for twenty-four adults and twelve children with mild to severe sensorineural hearing loss. Stimuli were amplified based on each listener’s audiogram with conventional processing (CP) with amplitude compression or with NFC and presented under headphones using a software-based hearing aid simulator. A modification of the speech intelligibility index (SII) was used to estimate audibility of information in frequency-lowered bands. The mean improvement in SII was compared to the mean improvement in speech recognition. Results All but two listeners experienced improvements in speech recognition with NFC compared to CP, consistent with the small increase in audibility that was estimated using the modification of the SII. Children and adults had similar improvements in speech recognition with NFC. Conclusion Word recognition with NFC was higher than CP for children and adults with mild to severe hearing loss. The average improvement in speech recognition with NFC (7%) was consistent with the modified SII, which indicated that listeners experienced an increase in audibility with NFC compared to CP. Further studies are necessary to determine if changes in audibility with NFC are related to speech recognition with NFC for listeners with greater degrees of hearing loss, with a greater variety of compression settings, and using auditory training. PMID:24535558

Hands-free device control using sound picked up in the ear canal

NASA Astrophysics Data System (ADS)

Chhatpar, Siddharth R.; Ngia, Lester; Vlach, Chris; Lin, Dong; Birkhimer, Craig; Juneja, Amit; Pruthi, Tarun; Hoffman, Orin; Lewis, Tristan

2008-04-01

Hands-free control of unmanned ground vehicles is essential for soldiers, bomb disposal squads, and first responders. Having their hands free for other equipment and tasks allows them to be safer and more mobile. Currently, the most successful hands-free control devices are speech-command based. However, these devices use external microphones, and in field environments, e.g., war zones and fire sites, their performance suffers because of loud ambient noise: typically above 90dBA. This paper describes the development of technology using the ear as an output source that can provide excellent command recognition accuracy even in noisy environments. Instead of picking up speech radiating from the mouth, this technology detects speech transmitted internally through the ear canal. Discreet tongue movements also create air pressure changes within the ear canal, and can be used for stealth control. A patented earpiece was developed with a microphone pointed into the ear canal that captures these signals generated by tongue movements and speech. The signals are transmitted from the earpiece to an Ultra-Mobile Personal Computer (UMPC) through a wired connection. The UMPC processes the signals and utilizes them for device control. The processing can include command recognition, ambient noise cancellation, acoustic echo cancellation, and speech equalization. Successful control of an iRobot PackBot has been demonstrated with both speech (13 discrete commands) and tongue (5 discrete commands) signals. In preliminary tests, command recognition accuracy was 95% with speech control and 85% with tongue control.

Accuracy of Cochlear Implant Recipients on Speech Reception in Background Music

PubMed Central

Gfeller, Kate; Turner, Christopher; Oleson, Jacob; Kliethermes, Stephanie; Driscoll, Virginia

2012-01-01

Objectives This study (a) examined speech recognition abilities of cochlear implant (CI) recipients in the spectrally complex listening condition of three contrasting types of background music, and (b) compared performance based upon listener groups: CI recipients using conventional long-electrode (LE) devices, Hybrid CI recipients (acoustic plus electric stimulation), and normal-hearing (NH) adults. Methods We tested 154 LE CI recipients using varied devices and strategies, 21 Hybrid CI recipients, and 49 NH adults on closed-set recognition of spondees presented in three contrasting forms of background music (piano solo, large symphony orchestra, vocal solo with small combo accompaniment) in an adaptive test. Outcomes Signal-to-noise thresholds for speech in music (SRTM) were examined in relation to measures of speech recognition in background noise and multi-talker babble, pitch perception, and music experience. Results SRTM thresholds varied as a function of category of background music, group membership (LE, Hybrid, NH), and age. Thresholds for speech in background music were significantly correlated with measures of pitch perception and speech in background noise thresholds; auditory status was an important predictor. Conclusions Evidence suggests that speech reception thresholds in background music change as a function of listener age (with more advanced age being detrimental), structural characteristics of different types of music, and hearing status (residual hearing). These findings have implications for everyday listening conditions such as communicating in social or commercial situations in which there is background music. PMID:23342550

Analysis of human scream and its impact on text-independent speaker verification.

PubMed

Hansen, John H L; Nandwana, Mahesh Kumar; Shokouhi, Navid

2017-04-01

Scream is defined as sustained, high-energy vocalizations that lack phonological structure. Lack of phonological structure is how scream is identified from other forms of loud vocalization, such as "yell." This study investigates the acoustic aspects of screams and addresses those that are known to prevent standard speaker identification systems from recognizing the identity of screaming speakers. It is well established that speaker variability due to changes in vocal effort and Lombard effect contribute to degraded performance in automatic speech systems (i.e., speech recognition, speaker identification, diarization, etc.). However, previous research in the general area of speaker variability has concentrated on human speech production, whereas less is known about non-speech vocalizations. The UT-NonSpeech corpus is developed here to investigate speaker verification from scream samples. This study considers a detailed analysis in terms of fundamental frequency, spectral peak shift, frame energy distribution, and spectral tilt. It is shown that traditional speaker recognition based on the Gaussian mixture models-universal background model framework is unreliable when evaluated with screams.

Effect of Acting Experience on Emotion Expression and Recognition in Voice: Non-Actors Provide Better Stimuli than Expected.

PubMed

Jürgens, Rebecca; Grass, Annika; Drolet, Matthis; Fischer, Julia

Both in the performative arts and in emotion research, professional actors are assumed to be capable of delivering emotions comparable to spontaneous emotional expressions. This study examines the effects of acting training on vocal emotion depiction and recognition. We predicted that professional actors express emotions in a more realistic fashion than non-professional actors. However, professional acting training may lead to a particular speech pattern; this might account for vocal expressions by actors that are less comparable to authentic samples than the ones by non-professional actors. We compared 80 emotional speech tokens from radio interviews with 80 re-enactments by professional and inexperienced actors, respectively. We analyzed recognition accuracies for emotion and authenticity ratings and compared the acoustic structure of the speech tokens. Both play-acted conditions yielded similar recognition accuracies and possessed more variable pitch contours than the spontaneous recordings. However, professional actors exhibited signs of different articulation patterns compared to non-trained speakers. Our results indicate that for emotion research, emotional expressions by professional actors are not better suited than those from non-actors.

How much does language proficiency by non-native listeners influence speech audiometric tests in noise?

PubMed

Warzybok, Anna; Brand, Thomas; Wagener, Kirsten C; Kollmeier, Birger

2015-01-01

The current study investigates the extent to which the linguistic complexity of three commonly employed speech recognition tests and second language proficiency influence speech recognition thresholds (SRTs) in noise in non-native listeners. SRTs were measured for non-natives and natives using three German speech recognition tests: the digit triplet test (DTT), the Oldenburg sentence test (OLSA), and the Göttingen sentence test (GÖSA). Sixty-four non-native and eight native listeners participated. Non-natives can show native-like SRTs in noise only for the linguistically easy speech material (DTT). Furthermore, the limitation of phonemic-acoustical cues in digit triplets affects speech recognition to the same extent in non-natives and natives. For more complex and less familiar speech materials, non-natives, ranging from basic to advanced proficiency in German, require on average 3-dB better signal-to-noise ratio for the OLSA and 6-dB for the GÖSA to obtain 50% speech recognition compared to native listeners. In clinical audiology, SRT measurements with a closed-set speech test (i.e. DTT for screening or OLSA test for clinical purposes) should be used with non-native listeners rather than open-set speech tests (such as the GÖSA or HINT), especially if a closed-set version in the patient's own native language is available.

Masking effects of speech and music: does the masker's hierarchical structure matter?

PubMed

Shi, Lu-Feng; Law, Yvonne

2010-04-01

Speech and music are time-varying signals organized by parallel hierarchical rules. Through a series of four experiments, this study compared the masking effects of single-talker speech and instrumental music on speech perception while manipulating the complexity of hierarchical and temporal structures of the maskers. Listeners' word recognition was found to be similar between hierarchically intact and disrupted speech or classical music maskers (Experiment 1). When sentences served as the signal, significantly greater masking effects were observed with disrupted than intact speech or classical music maskers (Experiment 2), although not with jazz or serial music maskers, which differed from the classical music masker in their hierarchical structures (Experiment 3). Removing the classical music masker's temporal dynamics or partially restoring it affected listeners' sentence recognition; yet, differences in performance between intact and disrupted maskers remained robust (Experiment 4). Hence, the effect of structural expectancy was largely present across maskers when comparing them before and after their hierarchical structure was purposefully disrupted. This effect seemed to lend support to the auditory stream segregation theory.

Mandarin-Speaking Children's Speech Recognition: Developmental Changes in the Influences of Semantic Context and F0 Contours.

PubMed

Zhou, Hong; Li, Yu; Liang, Meng; Guan, Connie Qun; Zhang, Linjun; Shu, Hua; Zhang, Yang

2017-01-01

The goal of this developmental speech perception study was to assess whether and how age group modulated the influences of high-level semantic context and low-level fundamental frequency ( F 0 ) contours on the recognition of Mandarin speech by elementary and middle-school-aged children in quiet and interference backgrounds. The results revealed different patterns for semantic and F 0 information. One the one hand, age group modulated significantly the use of F 0 contours, indicating that elementary school children relied more on natural F 0 contours than middle school children during Mandarin speech recognition. On the other hand, there was no significant modulation effect of age group on semantic context, indicating that children of both age groups used semantic context to assist speech recognition to a similar extent. Furthermore, the significant modulation effect of age group on the interaction between F 0 contours and semantic context revealed that younger children could not make better use of semantic context in recognizing speech with flat F 0 contours compared with natural F 0 contours, while older children could benefit from semantic context even when natural F 0 contours were altered, thus confirming the important role of F 0 contours in Mandarin speech recognition by elementary school children. The developmental changes in the effects of high-level semantic and low-level F 0 information on speech recognition might reflect the differences in auditory and cognitive resources associated with processing of the two types of information in speech perception.

Methods and apparatus for non-acoustic speech characterization and recognition

DOEpatents

Holzrichter, John F.

1999-01-01

By simultaneously recording EM wave reflections and acoustic speech information, the positions and velocities of the speech organs as speech is articulated can be defined for each acoustic speech unit. Well defined time frames and feature vectors describing the speech, to the degree required, can be formed. Such feature vectors can uniquely characterize the speech unit being articulated each time frame. The onset of speech, rejection of external noise, vocalized pitch periods, articulator conditions, accurate timing, the identification of the speaker, acoustic speech unit recognition, and organ mechanical parameters can be determined.

Methods and apparatus for non-acoustic speech characterization and recognition

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holzrichter, J.F.

By simultaneously recording EM wave reflections and acoustic speech information, the positions and velocities of the speech organs as speech is articulated can be defined for each acoustic speech unit. Well defined time frames and feature vectors describing the speech, to the degree required, can be formed. Such feature vectors can uniquely characterize the speech unit being articulated each time frame. The onset of speech, rejection of external noise, vocalized pitch periods, articulator conditions, accurate timing, the identification of the speaker, acoustic speech unit recognition, and organ mechanical parameters can be determined.

Voice technology and BBN

NASA Technical Reports Server (NTRS)

Wolf, Jared J.

1977-01-01

The following research was discussed: (1) speech signal processing; (2) automatic speech recognition; (3) continuous speech understanding; (4) speaker recognition; (5) speech compression; (6) subjective and objective evaluation of speech communication system; (7) measurement of the intelligibility and quality of speech when degraded by noise or other masking stimuli; (8) speech synthesis; (9) instructional aids for second-language learning and for training of the deaf; and (10) investigation of speech correlates of psychological stress. Experimental psychology, control systems, and human factors engineering, which are often relevant to the proper design and operation of speech systems are described.

Speech-on-speech masking with variable access to the linguistic content of the masker speech for native and nonnative english speakers.

PubMed

Calandruccio, Lauren; Bradlow, Ann R; Dhar, Sumitrajit

2014-04-01

Masking release for an English sentence-recognition task in the presence of foreign-accented English speech compared with native-accented English speech was reported in Calandruccio et al (2010a). The masking release appeared to increase as the masker intelligibility decreased. However, it could not be ruled out that spectral differences between the speech maskers were influencing the significant differences observed. The purpose of the current experiment was to minimize spectral differences between speech maskers to determine how various amounts of linguistic information within competing speech Affiliationect masking release. A mixed-model design with within-subject (four two-talker speech maskers) and between-subject (listener group) factors was conducted. Speech maskers included native-accented English speech and high-intelligibility, moderate-intelligibility, and low-intelligibility Mandarin-accented English. Normalizing the long-term average speech spectra of the maskers to each other minimized spectral differences between the masker conditions. Three listener groups were tested, including monolingual English speakers with normal hearing, nonnative English speakers with normal hearing, and monolingual English speakers with hearing loss. The nonnative English speakers were from various native language backgrounds, not including Mandarin (or any other Chinese dialect). Listeners with hearing loss had symmetric mild sloping to moderate sensorineural hearing loss. Listeners were asked to repeat back sentences that were presented in the presence of four different two-talker speech maskers. Responses were scored based on the key words within the sentences (100 key words per masker condition). A mixed-model regression analysis was used to analyze the difference in performance scores between the masker conditions and listener groups. Monolingual English speakers with normal hearing benefited when the competing speech signal was foreign accented compared with native accented, allowing for improved speech recognition. Various levels of intelligibility across the foreign-accented speech maskers did not influence results. Neither the nonnative English-speaking listeners with normal hearing nor the monolingual English speakers with hearing loss benefited from masking release when the masker was changed from native-accented to foreign-accented English. Slight modifications between the target and the masker speech allowed monolingual English speakers with normal hearing to improve their recognition of native-accented English, even when the competing speech was highly intelligible. Further research is needed to determine which modifications within the competing speech signal caused the Mandarin-accented English to be less effective with respect to masking. Determining the influences within the competing speech that make it less effective as a masker or determining why monolingual normal-hearing listeners can take advantage of these differences could help improve speech recognition for those with hearing loss in the future. American Academy of Audiology.

Comparison of the Spectral-Temporally Modulated Ripple Test With the Arizona Biomedical Institute Sentence Test in Cochlear Implant Users.

PubMed

Lawler, Marshall; Yu, Jeffrey; Aronoff, Justin M

Although speech perception is the gold standard for measuring cochlear implant (CI) users' performance, speech perception tests often require extensive adaptation to obtain accurate results, particularly after large changes in maps. Spectral ripple tests, which measure spectral resolution, are an alternate measure that has been shown to correlate with speech perception. A modified spectral ripple test, the spectral-temporally modulated ripple test (SMRT) has recently been developed, and the objective of this study was to compare speech perception and performance on the SMRT for a heterogeneous population of unilateral CI users, bilateral CI users, and bimodal users. Twenty-five CI users (eight using unilateral CIs, nine using bilateral CIs, and eight using a CI and a hearing aid) were tested on the Arizona Biomedical Institute Sentence Test (AzBio) with a +8 dB signal to noise ratio, and on the SMRT. All participants were tested with their clinical programs. There was a significant correlation between SMRT and AzBio performance. After a practice block, an improvement of one ripple per octave for SMRT corresponded to an improvement of 12.1% for AzBio. Additionally, there was no significant difference in slope or intercept between any of the CI populations. The results indicate that performance on the SMRT correlates with speech recognition in noise when measured across unilateral, bilateral, and bimodal CI populations. These results suggest that SMRT scores are strongly associated with speech recognition in noise ability in experienced CI users. Further studies should focus on increasing both the size and diversity of the tested participants, and on determining whether the SMRT technique can be used for early predictions of long-term speech scores, or for evaluating differences among different stimulation strategies or parameter settings.

Speech and gesture interfaces for squad-level human-robot teaming

NASA Astrophysics Data System (ADS)

Harris, Jonathan; Barber, Daniel

2014-06-01

As the military increasingly adopts semi-autonomous unmanned systems for military operations, utilizing redundant and intuitive interfaces for communication between Soldiers and robots is vital to mission success. Currently, Soldiers use a common lexicon to verbally and visually communicate maneuvers between teammates. In order for robots to be seamlessly integrated within mixed-initiative teams, they must be able to understand this lexicon. Recent innovations in gaming platforms have led to advancements in speech and gesture recognition technologies, but the reliability of these technologies for enabling communication in human robot teaming is unclear. The purpose for the present study is to investigate the performance of Commercial-Off-The-Shelf (COTS) speech and gesture recognition tools in classifying a Squad Level Vocabulary (SLV) for a spatial navigation reconnaissance and surveillance task. The SLV for this study was based on findings from a survey conducted with Soldiers at Fort Benning, GA. The items of the survey focused on the communication between the Soldier and the robot, specifically in regards to verbally instructing them to execute reconnaissance and surveillance tasks. Resulting commands, identified from the survey, were then converted to equivalent arm and hand gestures, leveraging existing visual signals (e.g. U.S. Army Field Manual for Visual Signaling). A study was then run to test the ability of commercially available automated speech recognition technologies and a gesture recognition glove to classify these commands in a simulated intelligence, surveillance, and reconnaissance task. This paper presents classification accuracy of these devices for both speech and gesture modalities independently.

Combined Electric and Contralateral Acoustic Hearing: Word and Sentence Recognition with Bimodal Hearing

ERIC Educational Resources Information Center

Gifford, Rene H.; Dorman, Michael F.; McKarns, Sharon A.; Spahr, Anthony J.

2007-01-01

Purpose: The authors assessed whether (a) a full-insertion cochlear implant would provide a higher level of speech understanding than bilateral low-frequency acoustic hearing, (b) contralateral acoustic hearing would add to the speech understanding provided by the implant, and (c) the level of performance achieved with electric stimulation plus…

Speech Recognition in Fluctuating and Continuous Maskers: Effects of Hearing Loss and Presentation Level.

ERIC Educational Resources Information Center

Summers, Van; Molis, Michelle R.

2004-01-01

Listeners with normal-hearing sensitivity recognize speech more accurately in the presence of fluctuating background sounds, such as a single competing voice, than in unmodulated noise at the same overall level. These performance differences ore greatly reduced in listeners with hearing impairment, who generally receive little benefit from…

Investigating Prompt Difficulty in an Automatically Scored Speaking Performance Assessment

ERIC Educational Resources Information Center

Cox, Troy L.

2013-01-01

Speaking assessments for second language learners have traditionally been expensive to administer because of the cost of rating the speech samples. To reduce the cost, many researchers are investigating the potential of using automatic speech recognition (ASR) as a means to score examinee responses to open-ended prompts. This study examined the…

The Role of Native-Language Knowledge in the Perception of Casual Speech in a Second Language

PubMed Central

Mitterer, Holger; Tuinman, Annelie

2012-01-01

Casual speech processes, such as /t/-reduction, make word recognition harder. Additionally, word recognition is also harder in a second language (L2). Combining these challenges, we investigated whether L2 learners have recourse to knowledge from their native language (L1) when dealing with casual speech processes in their L2. In three experiments, production and perception of /t/-reduction was investigated. An initial production experiment showed that /t/-reduction occurred in both languages and patterned similarly in proper nouns but differed when /t/ was a verbal inflection. Two perception experiments compared the performance of German learners of Dutch with that of native speakers for nouns and verbs. Mirroring the production patterns, German learners’ performance strongly resembled that of native Dutch listeners when the reduced /t/ was part of a word stem, but deviated where /t/ was a verbal inflection. These results suggest that a casual speech process in a second language is problematic for learners when the process is not known from the leaner’s native language, similar to what has been observed for phoneme contrasts. PMID:22811675

Speech Recognition and Cognitive Skills in Bimodal Cochlear Implant Users

ERIC Educational Resources Information Center

Hua, Håkan; Johansson, Björn; Magnusson, Lennart; Lyxell, Björn; Ellis, Rachel J.

2017-01-01

Purpose: To examine the relation between speech recognition and cognitive skills in bimodal cochlear implant (CI) and hearing aid users. Method: Seventeen bimodal CI users (28-74 years) were recruited to the study. Speech recognition tests were carried out in quiet and in noise. The cognitive tests employed included the Reading Span Test and the…

Leveraging Automatic Speech Recognition Errors to Detect Challenging Speech Segments in TED Talks

ERIC Educational Resources Information Center

Mirzaei, Maryam Sadat; Meshgi, Kourosh; Kawahara, Tatsuya

2016-01-01

This study investigates the use of Automatic Speech Recognition (ASR) systems to epitomize second language (L2) listeners' problems in perception of TED talks. ASR-generated transcripts of videos often involve recognition errors, which may indicate difficult segments for L2 listeners. This paper aims to discover the root-causes of the ASR errors…

Improved Open-Microphone Speech Recognition

NASA Astrophysics Data System (ADS)

Abrash, Victor

2002-12-01

Many current and future NASA missions make extreme demands on mission personnel both in terms of work load and in performing under difficult environmental conditions. In situations where hands are impeded or needed for other tasks, eyes are busy attending to the environment, or tasks are sufficiently complex that ease of use of the interface becomes critical, spoken natural language dialog systems offer unique input and output modalities that can improve efficiency and safety. They also offer new capabilities that would not otherwise be available. For example, many NASA applications require astronauts to use computers in micro-gravity or while wearing space suits. Under these circumstances, command and control systems that allow users to issue commands or enter data in hands-and eyes-busy situations become critical. Speech recognition technology designed for current commercial applications limits the performance of the open-ended state-of-the-art dialog systems being developed at NASA. For example, today's recognition systems typically listen to user input only during short segments of the dialog, and user input outside of these short time windows is lost. Mistakes detecting the start and end times of user utterances can lead to mistakes in the recognition output, and the dialog system as a whole has no way to recover from this, or any other, recognition error. Systems also often require the user to signal when that user is going to speak, which is impractical in a hands-free environment, or only allow a system-initiated dialog requiring the user to speak immediately following a system prompt. In this project, SRI has developed software to enable speech recognition in a hands-free, open-microphone environment, eliminating the need for a push-to-talk button or other signaling mechanism. The software continuously captures a user's speech and makes it available to one or more recognizers. By constantly monitoring and storing the audio stream, it provides the spoken dialog manager extra flexibility to recognize the signal with no audio gaps between recognition requests, as well as to rerecognize portions of the signal, or to rerecognize speech with different grammars, acoustic models, recognizers, start times, and so on. SRI expects that this new open-mic functionality will enable NASA to develop better error-correction mechanisms for spoken dialog systems, and may also enable new interaction strategies.

Improved Open-Microphone Speech Recognition

NASA Technical Reports Server (NTRS)

Abrash, Victor

2002-01-01

Many current and future NASA missions make extreme demands on mission personnel both in terms of work load and in performing under difficult environmental conditions. In situations where hands are impeded or needed for other tasks, eyes are busy attending to the environment, or tasks are sufficiently complex that ease of use of the interface becomes critical, spoken natural language dialog systems offer unique input and output modalities that can improve efficiency and safety. They also offer new capabilities that would not otherwise be available. For example, many NASA applications require astronauts to use computers in micro-gravity or while wearing space suits. Under these circumstances, command and control systems that allow users to issue commands or enter data in hands-and eyes-busy situations become critical. Speech recognition technology designed for current commercial applications limits the performance of the open-ended state-of-the-art dialog systems being developed at NASA. For example, today's recognition systems typically listen to user input only during short segments of the dialog, and user input outside of these short time windows is lost. Mistakes detecting the start and end times of user utterances can lead to mistakes in the recognition output, and the dialog system as a whole has no way to recover from this, or any other, recognition error. Systems also often require the user to signal when that user is going to speak, which is impractical in a hands-free environment, or only allow a system-initiated dialog requiring the user to speak immediately following a system prompt. In this project, SRI has developed software to enable speech recognition in a hands-free, open-microphone environment, eliminating the need for a push-to-talk button or other signaling mechanism. The software continuously captures a user's speech and makes it available to one or more recognizers. By constantly monitoring and storing the audio stream, it provides the spoken dialog manager extra flexibility to recognize the signal with no audio gaps between recognition requests, as well as to rerecognize portions of the signal, or to rerecognize speech with different grammars, acoustic models, recognizers, start times, and so on. SRI expects that this new open-mic functionality will enable NASA to develop better error-correction mechanisms for spoken dialog systems, and may also enable new interaction strategies.

Visual Speech Primes Open-Set Recognition of Spoken Words

ERIC Educational Resources Information Center

Buchwald, Adam B.; Winters, Stephen J.; Pisoni, David B.

2009-01-01

Visual speech perception has become a topic of considerable interest to speech researchers. Previous research has demonstrated that perceivers neurally encode and use speech information from the visual modality, and this information has been found to facilitate spoken word recognition in tasks such as lexical decision (Kim, Davis, & Krins,…

Design and performance of a large vocabulary discrete word recognition system. Volume 2: Appendixes. [flow charts and users manual

NASA Technical Reports Server (NTRS)

1973-01-01

The users manual for the word recognition computer program contains flow charts of the logical diagram, the memory map for templates, the speech analyzer card arrangement, minicomputer input/output routines, and assembly language program listings.

Clinical experience with the words-in-noise test on 3430 veterans: comparisons with pure-tone thresholds and word recognition in quiet.

PubMed

Wilson, Richard H

2011-01-01

Since the 1940s, measures of pure-tone sensitivity and speech recognition in quiet have been vital components of the audiologic evaluation. Although early investigators urged that speech recognition in noise also should be a component of the audiologic evaluation, only recently has this suggestion started to become a reality. This report focuses on the Words-in-Noise (WIN) Test, which evaluates word recognition in multitalker babble at seven signal-to-noise ratios and uses the 50% correct point (in dB SNR) calculated with the Spearman-Kärber equation as the primary metric. The WIN was developed and validated in a series of 12 laboratory studies. The current study examined the effectiveness of the WIN materials for measuring the word-recognition performance of patients in a typical clinical setting. To examine the relations among three audiometric measures including pure-tone thresholds, word-recognition performances in quiet, and word-recognition performances in multitalker babble for veterans seeking remediation for their hearing loss. Retrospective, descriptive. The participants were 3430 veterans who for the most part were evaluated consecutively in the Audiology Clinic at the VA Medical Center, Mountain Home, Tennessee. The mean age was 62.3 yr (SD = 12.8 yr). The data were collected in the course of a 60 min routine audiologic evaluation. A history, otoscopy, and aural-acoustic immittance measures also were included in the clinic protocol but were not evaluated in this report. Overall, the 1000-8000 Hz thresholds were significantly lower (better) in the right ear (RE) than in the left ear (LE). There was a direct relation between age and the pure-tone thresholds, with greater change across age in the high frequencies than in the low frequencies. Notched audiograms at 4000 Hz were observed in at least one ear in 41% of the participants with more unilateral than bilateral notches. Normal pure-tone thresholds (≤20 dB HL) were obtained from 6% of the participants. Maximum performance on the Northwestern University Auditory Test No. 6 (NU-6) in quiet was ≥90% correct by 50% of the participants, with an additional 20% performing at ≥80% correct; the RE performed 1-3% better than the LE. Of the 3291 who completed the WIN on both ears, only 7% exhibited normal performance (50% correct point of ≤6 dB SNR). Overall, WIN performance was significantly better in the RE (mean = 13.3 dB SNR) than in the LE (mean = 13.8 dB SNR). Recognition performance on both the NU-6 and the WIN decreased as a function of both pure-tone hearing loss and age. There was a stronger relation between the high-frequency pure-tone average (1000, 2000, and 4000 Hz) and the WIN than between the pure-tone average (500, 1000, and 2000 Hz) and the WIN. The results on the WIN from both the previous laboratory studies and the current clinical study indicate that the WIN is an appropriate clinic instrument to assess word-recognition performance in background noise. Recognition performance on a speech-in-quiet task does not predict performance on a speech-in-noise task, as the two tasks reflect different domains of auditory function. Experience with the WIN indicates that word-in-noise tasks should be considered the "stress test" for auditory function. American Academy of Audiology.

Current trends in small vocabulary speech recognition for equipment control

NASA Astrophysics Data System (ADS)

Doukas, Nikolaos; Bardis, Nikolaos G.

2017-09-01

Speech recognition systems allow human - machine communication to acquire an intuitive nature that approaches the simplicity of inter - human communication. Small vocabulary speech recognition is a subset of the overall speech recognition problem, where only a small number of words need to be recognized. Speaker independent small vocabulary recognition can find significant applications in field equipment used by military personnel. Such equipment may typically be controlled by a small number of commands that need to be given quickly and accurately, under conditions where delicate manual operations are difficult to achieve. This type of application could hence significantly benefit by the use of robust voice operated control components, as they would facilitate the interaction with their users and render it much more reliable in times of crisis. This paper presents current challenges involved in attaining efficient and robust small vocabulary speech recognition. These challenges concern feature selection, classification techniques, speaker diversity and noise effects. A state machine approach is presented that facilitates the voice guidance of different equipment in a variety of situations.

Right-Ear Advantage for Speech-in-Noise Recognition in Patients with Nonlateralized Tinnitus and Normal Hearing Sensitivity.

PubMed

Tai, Yihsin; Husain, Fatima T

2018-04-01

Despite having normal hearing sensitivity, patients with chronic tinnitus may experience more difficulty recognizing speech in adverse listening conditions as compared to controls. However, the association between the characteristics of tinnitus (severity and loudness) and speech recognition remains unclear. In this study, the Quick Speech-in-Noise test (QuickSIN) was conducted monaurally on 14 patients with bilateral tinnitus and 14 age- and hearing-matched adults to determine the relation between tinnitus characteristics and speech understanding. Further, Tinnitus Handicap Inventory (THI), tinnitus loudness magnitude estimation, and loudness matching were obtained to better characterize the perceptual and psychological aspects of tinnitus. The patients reported low THI scores, with most participants in the slight handicap category. Significant between-group differences in speech-in-noise performance were only found at the 5-dB signal-to-noise ratio (SNR) condition. The tinnitus group performed significantly worse in the left ear than in the right ear, even though bilateral tinnitus percept and symmetrical thresholds were reported in all patients. This between-ear difference is likely influenced by a right-ear advantage for speech sounds, as factors related to testing order and fatigue were ruled out. Additionally, significant correlations found between SNR loss in the left ear and tinnitus loudness matching suggest that perceptual factors related to tinnitus had an effect on speech-in-noise performance, pointing to a possible interaction between peripheral and cognitive factors in chronic tinnitus. Further studies, that take into account both hearing and cognitive abilities of patients, are needed to better parse out the effect of tinnitus in the absence of hearing impairment.

Impact of stimulus-related factors and hearing impairment on listening effort as indicated by pupil dilation.

PubMed

Ohlenforst, Barbara; Zekveld, Adriana A; Lunner, Thomas; Wendt, Dorothea; Naylor, Graham; Wang, Yang; Versfeld, Niek J; Kramer, Sophia E

2017-08-01

Previous research has reported effects of masker type and signal-to-noise ratio (SNR) on listening effort, as indicated by the peak pupil dilation (PPD) relative to baseline during speech recognition. At about 50% correct sentence recognition performance, increasing SNRs generally results in declining PPDs, indicating reduced effort. However, the decline in PPD over SNRs has been observed to be less pronounced for hearing-impaired (HI) compared to normal-hearing (NH) listeners. The presence of a competing talker during speech recognition generally resulted in larger PPDs as compared to the presence of a fluctuating or stationary background noise. The aim of the present study was to examine the interplay between hearing-status, a broad range of SNRs corresponding to sentence recognition performance varying from 0 to 100% correct, and different masker types (stationary noise and single-talker masker) on the PPD during speech perception. Twenty-five HI and 32 age-matched NH participants listened to sentences across a broad range of SNRs, masked with speech from a single talker (-25 dB to +15 dB SNR) or with stationary noise (-12 dB to +16 dB). Correct sentence recognition scores and pupil responses were recorded during stimulus presentation. With a stationary masker, NH listeners show maximum PPD across a relatively narrow range of low SNRs, while HI listeners show relatively large PPD across a wide range of ecological SNRs. With the single-talker masker, maximum PPD was observed in the mid-range of SNRs around 50% correct sentence recognition performance, while smaller PPDs were observed at lower and higher SNRs. Mixed-model ANOVAs revealed significant interactions between hearing-status and SNR on the PPD for both masker types. Our data show a different pattern of PPDs across SNRs between groups, which indicates that listening and the allocation of effort during listening in daily life environments may be different for NH and HI listeners. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Preschoolers Benefit From Visually Salient Speech Cues

PubMed Central

Holt, Rachael Frush

2015-01-01

Purpose This study explored visual speech influence in preschoolers using 3 developmentally appropriate tasks that vary in perceptual difficulty and task demands. They also examined developmental differences in the ability to use visually salient speech cues and visual phonological knowledge. Method Twelve adults and 27 typically developing 3- and 4-year-old children completed 3 audiovisual (AV) speech integration tasks: matching, discrimination, and recognition. The authors compared AV benefit for visually salient and less visually salient speech discrimination contrasts and assessed the visual saliency of consonant confusions in auditory-only and AV word recognition. Results Four-year-olds and adults demonstrated visual influence on all measures. Three-year-olds demonstrated visual influence on speech discrimination and recognition measures. All groups demonstrated greater AV benefit for the visually salient discrimination contrasts. AV recognition benefit in 4-year-olds and adults depended on the visual saliency of speech sounds. Conclusions Preschoolers can demonstrate AV speech integration. Their AV benefit results from efficient use of visually salient speech cues. Four-year-olds, but not 3-year-olds, used visual phonological knowledge to take advantage of visually salient speech cues, suggesting possible developmental differences in the mechanisms of AV benefit. PMID:25322336

Comparison of formant detection methods used in speech processing applications

NASA Astrophysics Data System (ADS)

Belean, Bogdan

2013-11-01

The paper describes time frequency representations of speech signal together with the formant significance in speech processing applications. Speech formants can be used in emotion recognition, sex discrimination or diagnosing different neurological diseases. Taking into account the various applications of formant detection in speech signal, two methods for detecting formants are presented. First, the poles resulted after a complex analysis of LPC coefficients are used for formants detection. The second approach uses the Kalman filter for formant prediction along the speech signal. Results are presented for both approaches on real life speech spectrograms. A comparison regarding the features of the proposed methods is also performed, in order to establish which method is more suitable in case of different speech processing applications.

Multivariate Predictors of Music Perception and Appraisal by Adult Cochlear Implant Users

PubMed Central

Gfeller, Kate; Oleson, Jacob; Knutson, John F.; Breheny, Patrick; Driscoll, Virginia; Olszewski, Carol

2009-01-01

The research examined whether performance by adult cochlear implant recipients on a variety of recognition and appraisal tests derived from real-world music could be predicted from technological, demographic, and life experience variables, as well as speech recognition scores. A representative sample of 209 adults implanted between 1985 and 2006 participated. Using multiple linear regression models and generalized linear mixed models, sets of optimal predictor variables were selected that effectively predicted performance on a test battery that assessed different aspects of music listening. These analyses established the importance of distinguishing between the accuracy of music perception and the appraisal of musical stimuli when using music listening as an index of implant success. Importantly, neither device type nor processing strategy predicted music perception or music appraisal. Speech recognition performance was not a strong predictor of music perception, and primarily predicted music perception when the test stimuli included lyrics. Additionally, limitations in the utility of speech perception in predicting musical perception and appraisal underscore the utility of music perception as an alternative outcome measure for evaluating implant outcomes. Music listening background, residual hearing (i.e., hearing aid use), cognitive factors, and some demographic factors predicted several indices of perceptual accuracy or appraisal of music. PMID:18669126

Clinical implications of word recognition differences in earphone and aided conditions

PubMed Central

McRackan, Theodore R.; Ahlstrom, Jayne B.; Clinkscales, William B.; Meyer, Ted A.; Dubno, Judy R

2017-01-01

Objective To compare word recognition scores for adults with hearing loss measured using earphones and in the sound field without and with hearing aids (HA) Study design Independent review of pre-surgical audiological data from an active middle ear implant (MEI) FDA clinical trial Setting Multicenter prospective FDA clinical trial Patients Ninety-four adult HA users Interventions/Main outcomes measured Pre-operative earphone, unaided and aided pure tone thresholds, word recognition scores, and speech intelligibility index. Results We performed an independent review of pre-surgical audiological data from a MEI FDA trial and compared unaided and aided word recognition scores with participants’ HAs fit according to the NAL-R algorithm. For 52 participants (55.3%), differences in scores between earphone and aided conditions were >10%; for 33 participants (35.1%), earphone scores were higher by 10% or more than aided scores. These participants had significantly higher pure tone thresholds at 250 Hz, 500 Hz, and 1000 Hz), higher pure tone averages, higher speech recognition thresholds, (and higher earphone speech levels (p=0.002). No significant correlation was observed between word recognition scores measured with earphones and with hearing aids (r=.14; p=0.16), whereas a moderately high positive correlation was observed between unaided and aided word recognition (r=0.68; p<0.001). Conclusion Results of the these analyses do not support the common clinical practice of using word recognition scores measured with earphones to predict aided word recognition or hearing aid benefit. Rather, these results provide evidence supporting the measurement of aided word recognition in patients who are considering hearing aids. PMID:27631832

An attention-gating recurrent working memory architecture for emergent speech representation

NASA Astrophysics Data System (ADS)

Elshaw, Mark; Moore, Roger K.; Klein, Michael

2010-06-01

This paper describes an attention-gating recurrent self-organising map approach for emergent speech representation. Inspired by evidence from human cognitive processing, the architecture combines two main neural components. The first component, the attention-gating mechanism, uses actor-critic learning to perform selective attention towards speech. Through this selective attention approach, the attention-gating mechanism controls access to working memory processing. The second component, the recurrent self-organising map memory, develops a temporal-distributed representation of speech using phone-like structures. Representing speech in terms of phonetic features in an emergent self-organised fashion, according to research on child cognitive development, recreates the approach found in infants. Using this representational approach, in a fashion similar to infants, should improve the performance of automatic recognition systems through aiding speech segmentation and fast word learning.

Unilateral Hearing Loss: Understanding Speech Recognition and Localization Variability - Implications for Cochlear Implant Candidacy

PubMed Central

Firszt, Jill B.; Reeder, Ruth M.; Holden, Laura K.

2016-01-01

Objectives At a minimum, unilateral hearing loss (UHL) impairs sound localization ability and understanding speech in noisy environments, particularly if the loss is severe to profound. Accompanying the numerous negative consequences of UHL is considerable unexplained individual variability in the magnitude of its effects. Identification of co-variables that affect outcome and contribute to variability in UHLs could augment counseling, treatment options, and rehabilitation. Cochlear implantation as a treatment for UHL is on the rise yet little is known about factors that could impact performance or whether there is a group at risk for poor cochlear implant outcomes when hearing is near-normal in one ear. The overall goal of our research is to investigate the range and source of variability in speech recognition in noise and localization among individuals with severe to profound UHL and thereby help determine factors relevant to decisions regarding cochlear implantation in this population. Design The present study evaluated adults with severe to profound UHL and adults with bilateral normal hearing. Measures included adaptive sentence understanding in diffuse restaurant noise, localization, roving-source speech recognition (words from 1 of 15 speakers in a 140° arc) and an adaptive speech-reception threshold psychoacoustic task with varied noise types and noise-source locations. There were three age-gender-matched groups: UHL (severe to profound hearing loss in one ear and normal hearing in the contralateral ear), normal hearing listening bilaterally, and normal hearing listening unilaterally. Results Although the normal-hearing-bilateral group scored significantly better and had less performance variability than UHLs on all measures, some UHL participants scored within the range of the normal-hearing-bilateral group on all measures. The normal-hearing participants listening unilaterally had better monosyllabic word understanding than UHLs for words presented on the blocked/deaf side but not the open/hearing side. In contrast, UHLs localized better than the normal hearing unilateral listeners for stimuli on the open/hearing side but not the blocked/deaf side. This suggests that UHLs had learned strategies for improved localization on the side of the intact ear. The UHL and unilateral normal hearing participant groups were not significantly different for speech-in-noise measures. UHL participants with childhood rather than recent hearing loss onset localized significantly better; however, these two groups did not differ for speech recognition in noise. Age at onset in UHL adults appears to affect localization ability differently than understanding speech in noise. Hearing thresholds were significantly correlated with speech recognition for UHL participants but not the other two groups. Conclusions Auditory abilities of UHLs varied widely and could be explained only in part by hearing threshold levels. Age at onset and length of hearing loss influenced performance on some, but not all measures. Results support the need for a revised and diverse set of clinical measures, including sound localization, understanding speech in varied environments and careful consideration of functional abilities as individuals with severe to profound UHL are being considered potential cochlear implant candidates. PMID:28067750

Speech coding, reconstruction and recognition using acoustics and electromagnetic waves

DOEpatents

Holzrichter, J.F.; Ng, L.C.

1998-03-17

The use of EM radiation in conjunction with simultaneously recorded acoustic speech information enables a complete mathematical coding of acoustic speech. The methods include the forming of a feature vector for each pitch period of voiced speech and the forming of feature vectors for each time frame of unvoiced, as well as for combined voiced and unvoiced speech. The methods include how to deconvolve the speech excitation function from the acoustic speech output to describe the transfer function each time frame. The formation of feature vectors defining all acoustic speech units over well defined time frames can be used for purposes of speech coding, speech compression, speaker identification, language-of-speech identification, speech recognition, speech synthesis, speech translation, speech telephony, and speech teaching. 35 figs.

Speech coding, reconstruction and recognition using acoustics and electromagnetic waves

DOEpatents

Holzrichter, John F.; Ng, Lawrence C.

1998-01-01

The use of EM radiation in conjunction with simultaneously recorded acoustic speech information enables a complete mathematical coding of acoustic speech. The methods include the forming of a feature vector for each pitch period of voiced speech and the forming of feature vectors for each time frame of unvoiced, as well as for combined voiced and unvoiced speech. The methods include how to deconvolve the speech excitation function from the acoustic speech output to describe the transfer function each time frame. The formation of feature vectors defining all acoustic speech units over well defined time frames can be used for purposes of speech coding, speech compression, speaker identification, language-of-speech identification, speech recognition, speech synthesis, speech translation, speech telephony, and speech teaching.

Effects of emotional and perceptual-motor stress on a voice recognition system's accuracy: An applied investigation

NASA Astrophysics Data System (ADS)

Poock, G. K.; Martin, B. J.

1984-02-01

This was an applied investigation examining the ability of a speech recognition system to recognize speakers' inputs when the speakers were under different stress levels. Subjects were asked to speak to a voice recognition system under three conditions: (1) normal office environment, (2) emotional stress, and (3) perceptual-motor stress. Results indicate a definite relationship between voice recognition system performance and the type of low stress reference patterns used to achieve recognition.

Monopolar Detection Thresholds Predict Spatial Selectivity of Neural Excitation in Cochlear Implants: Implications for Speech Recognition

PubMed Central

2016-01-01

The objectives of the study were to (1) investigate the potential of using monopolar psychophysical detection thresholds for estimating spatial selectivity of neural excitation with cochlear implants and to (2) examine the effect of site removal on speech recognition based on the threshold measure. Detection thresholds were measured in Cochlear Nucleus® device users using monopolar stimulation for pulse trains that were of (a) low rate and long duration, (b) high rate and short duration, and (c) high rate and long duration. Spatial selectivity of neural excitation was estimated by a forward-masking paradigm, where the probe threshold elevation in the presence of a forward masker was measured as a function of masker-probe separation. The strength of the correlation between the monopolar thresholds and the slopes of the masking patterns systematically reduced as neural response of the threshold stimulus involved interpulse interactions (refractoriness and sub-threshold adaptation), and spike-rate adaptation. Detection threshold for the low-rate stimulus most strongly correlated with the spread of forward masking patterns and the correlation reduced for long and high rate pulse trains. The low-rate thresholds were then measured for all electrodes across the array for each subject. Subsequently, speech recognition was tested with experimental maps that deactivated five stimulation sites with the highest thresholds and five randomly chosen ones. Performance with deactivating the high-threshold sites was better than performance with the subjects’ clinical map used every day with all electrodes active, in both quiet and background noise. Performance with random deactivation was on average poorer than that with the clinical map but the difference was not significant. These results suggested that the monopolar low-rate thresholds are related to the spatial neural excitation patterns in cochlear implant users and can be used to select sites for more optimal speech recognition performance. PMID:27798658

Comparison of speech perception performance between Sprint/Esprit 3G and Freedom processors in children implanted with nucleus cochlear implants.

PubMed

Santarelli, Rosamaria; Magnavita, Vincenzo; De Filippi, Roberta; Ventura, Laura; Genovese, Elisabetta; Arslan, Edoardo

2009-04-01

To compare speech perception performance in children fitted with previous generation Nucleus sound processor, Sprint or Esprit 3G, and the Freedom, the most recently released system from the Cochlear Corporation that features a larger input dynamic range. Prospective intrasubject comparative study. University Medical Center. Seventeen prelingually deafened children who had received the Nucleus 24 cochlear implant and used the Sprint or Esprit 3G sound processor. Cochlear implantation with Cochlear device. Speech perception was evaluated at baseline (Sprint, n = 11; Esprit 3G, n = 6) and after 1 month's experience with the Freedom sound processor. Identification and recognition of disyllabic words and identification of vowels were performed via recorded voice in quiet (70 dB [A]), in the presence of background noise at various levels of signal-to-noise ratio (+10, +5, 0, -5) and at a soft presentation level (60 dB [A]). Consonant identification and recognition of disyllabic words, trisyllabic words, and sentences were evaluated in live voice. Frequency discrimination was measured in a subset of subjects (n = 5) by using an adaptive, 3-interval, 3-alternative, forced-choice procedure. Identification of disyllabic words administered at a soft presentation level showed a significant increase when switching to the Freedom compared with the previously worn processor in children using the Sprint or Esprit 3G. Identification and recognition of disyllabic words in the presence of background noise as well as consonant identification and sentence recognition increased significantly for the Freedom compared with the previously worn device only in children fitted with the Sprint. Frequency discrimination was significantly better when switching to the Freedom compared with the previously worn processor. Serial comparisons revealed that that speech perception performance evaluated in children aged 5 to 15 years was superior with the Freedom than previous generations of Nucleus sound processors. These differences are deemed to ensue from an increased input dynamic range, a feature that offers potentially enhanced phonemic discrimination.

Characteristics of speaking style and implications for speech recognition.

PubMed

Shinozaki, Takahiro; Ostendorf, Mari; Atlas, Les

2009-09-01

Differences in speaking style are associated with more or less spectral variability, as well as different modulation characteristics. The greater variation in some styles (e.g., spontaneous speech and infant-directed speech) poses challenges for recognition but possibly also opportunities for learning more robust models, as evidenced by prior work and motivated by child language acquisition studies. In order to investigate this possibility, this work proposes a new method for characterizing speaking style (the modulation spectrum), examines spontaneous, read, adult-directed, and infant-directed styles in this space, and conducts pilot experiments in style detection and sampling for improved speech recognizer training. Speaking style classification is improved by using the modulation spectrum in combination with standard pitch and energy variation. Speech recognition experiments on a small vocabulary conversational speech recognition task show that sampling methods for training with a small amount of data benefit from the new features.

How should a speech recognizer work?

PubMed

Scharenborg, Odette; Norris, Dennis; Bosch, Louis; McQueen, James M

2005-11-12

Although researchers studying human speech recognition (HSR) and automatic speech recognition (ASR) share a common interest in how information processing systems (human or machine) recognize spoken language, there is little communication between the two disciplines. We suggest that this lack of communication follows largely from the fact that research in these related fields has focused on the mechanics of how speech can be recognized. In Marr's (1982) terms, emphasis has been on the algorithmic and implementational levels rather than on the computational level. In this article, we provide a computational-level analysis of the task of speech recognition, which reveals the close parallels between research concerned with HSR and ASR. We illustrate this relation by presenting a new computational model of human spoken-word recognition, built using techniques from the field of ASR that, in contrast to current existing models of HSR, recognizes words from real speech input. 2005 Lawrence Erlbaum Associates, Inc.

Speech recognition: how good is good enough?

PubMed

Krohn, Richard

2002-03-01

Since its infancy in the early 1990s, the technology of speech recognition has undergone a rapid evolution. Not only has the reliability of the programming improved dramatically, the return on investment has become increasingly compelling. The author describes some of the latest health care applications of speech-recognition technology, and how the next advances will be made in this area.

Effect of training on word-recognition performance in noise for young normal-hearing and older hearing-impaired listeners.

PubMed

Burk, Matthew H; Humes, Larry E; Amos, Nathan E; Strauser, Lauren E

2006-06-01

The objective of this study was to evaluate the effectiveness of a training program for hearing-impaired listeners to improve their speech-recognition performance within a background noise when listening to amplified speech. Both noise-masked young normal-hearing listeners, used to model the performance of elderly hearing-impaired listeners, and a group of elderly hearing-impaired listeners participated in the study. Of particular interest was whether training on an isolated word list presented by a standardized talker can generalize to everyday speech communication across novel talkers. Word-recognition performance was measured for both young normal-hearing (n = 16) and older hearing-impaired (n = 7) adults. Listeners were trained on a set of 75 monosyllabic words spoken by a single female talker over a 9- to 14-day period. Performance for the familiar (trained) talker was measured before and after training in both open-set and closed-set response conditions. Performance on the trained words of the familiar talker were then compared with those same words spoken by three novel talkers and to performance on a second set of untrained words presented by both the familiar and unfamiliar talkers. The hearing-impaired listeners returned 6 mo after their initial training to examine retention of the trained words as well as their ability to transfer any knowledge gained from word training to sentences containing both trained and untrained words. Both young normal-hearing and older hearing-impaired listeners performed significantly better on the word list in which they were trained versus a second untrained list presented by the same talker. Improvements on the untrained words were small but significant, indicating some generalization to novel words. The large increase in performance on the trained words, however, was maintained across novel talkers, pointing to the listener's greater focus on lexical memorization of the words rather than a focus on talker-specific acoustic characteristics. On return in 6 mo, listeners performed significantly better on the trained words relative to their initial baseline performance. Although the listeners performed significantly better on trained versus untrained words in isolation, once the trained words were embedded in sentences, no improvement in recognition over untrained words within the same sentences was shown. Older hearing-impaired listeners were able to significantly improve their word-recognition abilities through training with one talker and to the same degree as young normal-hearing listeners. The improved performance was maintained across talkers and across time. This might imply that training a listener using a standardized list and talker may still provide benefit when these same words are presented by novel talkers outside the clinic. However, training on isolated words was not sufficient to transfer to fluent speech for the specific sentence materials used within this study. Further investigation is needed regarding approaches to improve a hearing aid user's speech understanding in everyday communication situations.

Results with cochlear implantation in adults with speech recognition scores exceeding current criteria.

PubMed

Amoodi, Hosam A; Mick, Paul T; Shipp, David B; Friesen, Lendra M; Nedzelski, Julian M; Chen, Joseph M; Lin, Vincent Y W

2012-01-01

The primary purpose of this study was to evaluate a group of postlingually deafened adults, whose aided speech recognition exceeded commonly accepted candidacy criteria for implantation. The study aimed to define performance and qualitative outcomes of cochlear implants in these individuals compared with their optimally fitted hearing aid(s). Retrospective case series. Tertiary referral center. All postlingually deafened subjects (N = 27), who were unsuccessful hearing aid users implanted between 2000 and 2010 with a preimplantation Hearing in Noise Test (HINT) score of 60% or more were included. We compared patients' preoperative performance (HINT score) with hearing aids to postoperative performance with the cochlear implant after 12 months of device use. In addition, the Hearing Handicap Inventory questionnaire was used to quantify the hearing-related handicap change perceived after the implantation. The study group demonstrated significant postoperative improvement on all outcome measures; most notably, the mean HINT score improved from 68.4% (standard deviation, 8.3) to 91.9% (standard deviation, 9.7). Additionally, there was a significant improvement in hearing-related handicap perceived by all patients. The envelope of implantation candidacy criteria continues to expand as shown by this study's cohort. Patient satisfaction and speech recognition results are very encouraging in support of treating those who currently perform at a level above the conventional candidacy threshold but struggle with optimally fitted hearing aids.

On the Development of Speech Resources for the Mixtec Language

PubMed Central

2013-01-01

The Mixtec language is one of the main native languages in Mexico. In general, due to urbanization, discrimination, and limited attempts to promote the culture, the native languages are disappearing. Most of the information available about the Mixtec language is in written form as in dictionaries which, although including examples about how to pronounce the Mixtec words, are not as reliable as listening to the correct pronunciation from a native speaker. Formal acoustic resources, as speech corpora, are almost non-existent for the Mixtec, and no speech technologies are known to have been developed for it. This paper presents the development of the following resources for the Mixtec language: (1) a speech database of traditional narratives of the Mixtec culture spoken by a native speaker (labelled at the phonetic and orthographic levels by means of spectral analysis) and (2) a native speaker-adaptive automatic speech recognition (ASR) system (trained with the speech database) integrated with a Mixtec-to-Spanish/Spanish-to-Mixtec text translator. The speech database, although small and limited to a single variant, was reliable enough to build the multiuser speech application which presented a mean recognition/translation performance up to 94.36% in experiments with non-native speakers (the target users). PMID:23710134

The effect of presentation level and stimulation rate on speech perception and modulation detection for cochlear implant users.

PubMed

Brochier, Tim; McDermott, Hugh J; McKay, Colette M

2017-06-01

In order to improve speech understanding for cochlear implant users, it is important to maximize the transmission of temporal information. The combined effects of stimulation rate and presentation level on temporal information transfer and speech understanding remain unclear. The present study systematically varied presentation level (60, 50, and 40 dBA) and stimulation rate [500 and 2400 pulses per second per electrode (pps)] in order to observe how the effect of rate on speech understanding changes for different presentation levels. Speech recognition in quiet and noise, and acoustic amplitude modulation detection thresholds (AMDTs) were measured with acoustic stimuli presented to speech processors via direct audio input (DAI). With the 500 pps processor, results showed significantly better performance for consonant-vowel nucleus-consonant words in quiet, and a reduced effect of noise on sentence recognition. However, no rate or level effect was found for AMDTs, perhaps partly because of amplitude compression in the sound processor. AMDTs were found to be strongly correlated with the effect of noise on sentence perception at low levels. These results indicate that AMDTs, at least when measured with the CP910 Freedom speech processor via DAI, explain between-subject variance of speech understanding, but do not explain within-subject variance for different rates and levels.

Parametric Representation of the Speaker's Lips for Multimodal Sign Language and Speech Recognition

NASA Astrophysics Data System (ADS)

Ryumin, D.; Karpov, A. A.

2017-05-01

In this article, we propose a new method for parametric representation of human's lips region. The functional diagram of the method is described and implementation details with the explanation of its key stages and features are given. The results of automatic detection of the regions of interest are illustrated. A speed of the method work using several computers with different performances is reported. This universal method allows applying parametrical representation of the speaker's lipsfor the tasks of biometrics, computer vision, machine learning, and automatic recognition of face, elements of sign languages, and audio-visual speech, including lip-reading.

Computational Modeling of Emotions and Affect in Social-Cultural Interaction

DTIC Science & Technology

2013-10-02

acoustic and textual information sources. Second, a cross-lingual study was performed that shed light on how human perception and automatic recognition...speech is produced, a speaker’s pitch and intonational pattern, and word usage. Better feature representation and advanced approaches were used to...recognition performance, and improved our understanding of language/cultural impact on human perception of emotion and automatic classification. • Units

Evaluation of Adaptive Noise Management Technologies for School-Age Children with Hearing Loss.

PubMed

Wolfe, Jace; Duke, Mila; Schafer, Erin; Jones, Christine; Rakita, Lori

2017-05-01

Children with hearing loss experience significant difficulty understanding speech in noisy and reverberant situations. Adaptive noise management technologies, such as fully adaptive directional microphones and digital noise reduction, have the potential to improve communication in noise for children with hearing aids. However, there are no published studies evaluating the potential benefits children receive from the use of adaptive noise management technologies in simulated real-world environments as well as in daily situations. The objective of this study was to compare speech recognition, speech intelligibility ratings (SIRs), and sound preferences of children using hearing aids equipped with and without adaptive noise management technologies. A single-group, repeated measures design was used to evaluate performance differences obtained in four simulated environments. In each simulated environment, participants were tested in a basic listening program with minimal noise management features, a manual program designed for that scene, and the hearing instruments' adaptive operating system that steered hearing instrument parameterization based on the characteristics of the environment. Twelve children with mild to moderately severe sensorineural hearing loss. Speech recognition and SIRs were evaluated in three hearing aid programs with and without noise management technologies across two different test sessions and various listening environments. Also, the participants' perceptual hearing performance in daily real-world listening situations with two of the hearing aid programs was evaluated during a four- to six-week field trial that took place between the two laboratory sessions. On average, the use of adaptive noise management technology improved sentence recognition in noise for speech presented in front of the participant but resulted in a decrement in performance for signals arriving from behind when the participant was facing forward. However, the improvement with adaptive noise management exceeded the decrement obtained when the signal arrived from behind. Most participants reported better subjective SIRs when using adaptive noise management technologies, particularly when the signal of interest arrived from in front of the listener. In addition, most participants reported a preference for the technology with an automatically switching, adaptive directional microphone and adaptive noise reduction in real-world listening situations when compared to conventional, omnidirectional microphone use with minimal noise reduction processing. Use of the adaptive noise management technologies evaluated in this study improves school-age children's speech recognition in noise for signals arriving from the front. Although a small decrement in speech recognition in noise was observed for signals arriving from behind the listener, most participants reported a preference for use of noise management technology both when the signal arrived from in front and from behind the child. The results of this study suggest that adaptive noise management technologies should be considered for use with school-age children when listening in academic and social situations. American Academy of Audiology

Strength Is in Numbers: Can Concordant Artificial Listeners Improve Prediction of Emotion from Speech?

PubMed Central

Martinelli, Eugenio; Mencattini, Arianna; Di Natale, Corrado

2016-01-01

Humans can communicate their emotions by modulating facial expressions or the tone of their voice. Albeit numerous applications exist that enable machines to read facial emotions and recognize the content of verbal messages, methods for speech emotion recognition are still in their infancy. Yet, fast and reliable applications for emotion recognition are the obvious advancement of present ‘intelligent personal assistants’, and may have countless applications in diagnostics, rehabilitation and research. Taking inspiration from the dynamics of human group decision-making, we devised a novel speech emotion recognition system that applies, for the first time, a semi-supervised prediction model based on consensus. Three tests were carried out to compare this algorithm with traditional approaches. Labeling performances relative to a public database of spontaneous speeches are reported. The novel system appears to be fast, robust and less computationally demanding than traditional methods, allowing for easier implementation in portable voice-analyzers (as used in rehabilitation, research, industry, etc.) and for applications in the research domain (such as real-time pairing of stimuli to participants’ emotional state, selective/differential data collection based on emotional content, etc.). PMID:27563724

Listening Effort and Speech Recognition with Frequency Compression Amplification for Children and Adults with Hearing Loss.

PubMed

Brennan, Marc A; Lewis, Dawna; McCreery, Ryan; Kopun, Judy; Alexander, Joshua M

2017-10-01

Nonlinear frequency compression (NFC) can improve the audibility of high-frequency sounds by lowering them to a frequency where audibility is better; however, this lowering results in spectral distortion. Consequently, performance is a combination of the effects of increased access to high-frequency sounds and the detrimental effects of spectral distortion. Previous work has demonstrated positive benefits of NFC on speech recognition when NFC is set to improve audibility while minimizing distortion. However, the extent to which NFC impacts listening effort is not well understood, especially for children with sensorineural hearing loss (SNHL). To examine the impact of NFC on recognition and listening effort for speech in adults and children with SNHL. Within-subject, quasi-experimental study. Participants listened to amplified nonsense words that were (1) frequency-lowered using NFC, (2) low-pass filtered at 5 kHz to simulate the restricted bandwidth (RBW) of conventional hearing aid processing, or (3) low-pass filtered at 10 kHz to simulate extended bandwidth (EBW) amplification. Fourteen children (8-16 yr) and 14 adults (19-65 yr) with mild-to-severe SNHL. Participants listened to speech processed by a hearing aid simulator that amplified input signals to fit a prescriptive target fitting procedure. Participants were blinded to the type of processing. Participants' responses to each nonsense word were analyzed for accuracy and verbal-response time (VRT; listening effort). A multivariate analysis of variance and linear mixed model were used to determine the effect of hearing-aid signal processing on nonsense word recognition and VRT. Both children and adults identified the nonsense words and initial consonants better with EBW and NFC than with RBW. The type of processing did not affect the identification of the vowels or final consonants. There was no effect of age on recognition of the nonsense words, initial consonants, medial vowels, or final consonants. VRT did not change significantly with the type of processing or age. Both adults and children demonstrated improved speech recognition with access to the high-frequency sounds in speech. Listening effort as measured by VRT was not affected by access to high-frequency sounds. American Academy of Audiology

Speech coding, reconstruction and recognition using acoustics and electromagnetic waves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holzrichter, J.F.; Ng, L.C.

The use of EM radiation in conjunction with simultaneously recorded acoustic speech information enables a complete mathematical coding of acoustic speech. The methods include the forming of a feature vector for each pitch period of voiced speech and the forming of feature vectors for each time frame of unvoiced, as well as for combined voiced and unvoiced speech. The methods include how to deconvolve the speech excitation function from the acoustic speech output to describe the transfer function each time frame. The formation of feature vectors defining all acoustic speech units over well defined time frames can be used formore » purposes of speech coding, speech compression, speaker identification, language-of-speech identification, speech recognition, speech synthesis, speech translation, speech telephony, and speech teaching. 35 figs.« less

Female voice communications in high level aircraft cockpit noises--part II: vocoder and automatic speech recognition systems.

PubMed

Nixon, C; Anderson, T; Morris, L; McCavitt, A; McKinley, R; Yeager, D; McDaniel, M

1998-11-01

The intelligibility of female and male speech is equivalent under most ordinary living conditions. However, due to small differences between their acoustic speech signals, called speech spectra, one can be more or less intelligible than the other in certain situations such as high levels of noise. Anecdotal information, supported by some empirical observations, suggests that some of the high intensity noise spectra of military aircraft cockpits may degrade the intelligibility of female speech more than that of male speech. In an applied research study, the intelligibility of female and male speech was measured in several high level aircraft cockpit noise conditions experienced in military aviation. In Part I, (Nixon CW, et al. Aviat Space Environ Med 1998; 69:675-83) female speech intelligibility measured in the spectra and levels of aircraft cockpit noises and with noise-canceling microphones was lower than that of the male speech in all conditions. However, the differences were small and only those at some of the highest noise levels were significant. Although speech intelligibility of both genders was acceptable during normal cruise noises, improvements are required in most of the highest levels of noise created during maximum aircraft operating conditions. These results are discussed in a Part I technical report. This Part II report examines the intelligibility in the same aircraft cockpit noises of vocoded female and male speech and the accuracy with which female and male speech in some of the cockpit noises were understood by automatic speech recognition systems. The intelligibility of vocoded female speech was generally the same as that of vocoded male speech. No significant differences were measured between the recognition accuracy of male and female speech by the automatic speech recognition systems. The intelligibility of female and male speech was equivalent for these conditions.

Functional connectivity between face-movement and speech-intelligibility areas during auditory-only speech perception.

PubMed

Schall, Sonja; von Kriegstein, Katharina

2014-01-01

It has been proposed that internal simulation of the talking face of visually-known speakers facilitates auditory speech recognition. One prediction of this view is that brain areas involved in auditory-only speech comprehension interact with visual face-movement sensitive areas, even under auditory-only listening conditions. Here, we test this hypothesis using connectivity analyses of functional magnetic resonance imaging (fMRI) data. Participants (17 normal participants, 17 developmental prosopagnosics) first learned six speakers via brief voice-face or voice-occupation training (<2 min/speaker). This was followed by an auditory-only speech recognition task and a control task (voice recognition) involving the learned speakers' voices in the MRI scanner. As hypothesized, we found that, during speech recognition, familiarity with the speaker's face increased the functional connectivity between the face-movement sensitive posterior superior temporal sulcus (STS) and an anterior STS region that supports auditory speech intelligibility. There was no difference between normal participants and prosopagnosics. This was expected because previous findings have shown that both groups use the face-movement sensitive STS to optimize auditory-only speech comprehension. Overall, the present findings indicate that learned visual information is integrated into the analysis of auditory-only speech and that this integration results from the interaction of task-relevant face-movement and auditory speech-sensitive areas.

Evaluation of tooth-click triggering and speech recognition in assistive technology for computer access.

PubMed

Simpson, Tyler; Gauthier, Michel; Prochazka, Arthur

2010-02-01

Computer access can play an important role in employment and leisure activities following spinal cord injury. The authors' prior work has shown that a tooth-click detecting device, when paired with an optical head mouse, may be used by people with tetraplegia for controlling cursor movement and mouse button clicks. To compare the efficacy of tooth clicks to speech recognition and that of an optical head mouse to a gyrometer head mouse for cursor and mouse button control of a computer. Six able-bodied and 3 tetraplegic subjects used the devices listed above to produce cursor movements and mouse clicks in response to a series of prompts displayed on a computer. The time taken to move to and click on each target was recorded. The use of tooth clicks in combination with either an optical head mouse or a gyrometer head mouse can provide hands-free cursor movement and mouse button control at a speed of up to 22% of that of a standard mouse. Tooth clicks were significantly faster at generating mouse button clicks than speech recognition when paired with either type of head mouse device. Tooth-click detection performed better than speech recognition when paired with both the optical head mouse and the gyrometer head mouse. Such a system may improve computer access for people with tetraplegia.

Robot Command Interface Using an Audio-Visual Speech Recognition System

NASA Astrophysics Data System (ADS)

Ceballos, Alexánder; Gómez, Juan; Prieto, Flavio; Redarce, Tanneguy

In recent years audio-visual speech recognition has emerged as an active field of research thanks to advances in pattern recognition, signal processing and machine vision. Its ultimate goal is to allow human-computer communication using voice, taking into account the visual information contained in the audio-visual speech signal. This document presents a command's automatic recognition system using audio-visual information. The system is expected to control the laparoscopic robot da Vinci. The audio signal is treated using the Mel Frequency Cepstral Coefficients parametrization method. Besides, features based on the points that define the mouth's outer contour according to the MPEG-4 standard are used in order to extract the visual speech information.

Evaluation on health-related quality of life in deaf children with cochlear implant in China.

PubMed

Liu, Hong; Liu, Hong-Xiang; Kang, Hou-Yong; Gu, Zheng; Hong, Su-Ling

2016-09-01

Previous studies have shown that deaf children benefit considerably from cochlear implants. These improvements are found in areas such as speech perception, speech production, and audiology-verbal performance. Despite the increasing prevalence of cochlear implants in China, few studies have reported on health-related quality of life in children with cochlear implants. The main objective of this study was to explore health-related quality of life on children with cochlear implants in South-west China. A retrospective observational study of 213 CI users in Southwest China between 2010 and 2013. Participants were 213 individuals with bilateral severe-to-profound hearing loss who wore unilateral cochlear implants. The Nijmegen Cochlear Implant Questionnaire and Health Utility Index Mark III were used pre-implantation and 1 year post-implantation. Additionally, 1-year postoperative scores for Mandarin speech perception were compared with preoperative scores. Health-related quality of life improved post-operation with scores on the Nijmegen Cochlear Implant Questionnaire improving significantly in all subdomains, and the Health Utility Index 3 showing a significant improvement in the utility score and the subdomains of ''hearing," ''speech," and "emotion". Additionally, a significant improvement in speech recognition scores was found. No significant correlation was found between increased in quality of life and speech perception scores. Health-related quality of life and speech recognition in prelingual deaf children significantly improved post-operation. The lack of correlation between quality of life and speech perception suggests that when evaluating performance post-implantation in prelingual deaf children and adolescents, measures of both speech perception and quality of life should be used. Copyright © 2016. Published by Elsevier Ireland Ltd.

Speech-on-speech masking with variable access to the linguistic content of the masker speech for native and non-native speakers of English

PubMed Central

Calandruccio, Lauren; Bradlow, Ann R.; Dhar, Sumitrajit

2013-01-01

Background Masking release for an English sentence-recognition task in the presence of foreign-accented English speech compared to native-accented English speech was reported in Calandruccio, Dhar and Bradlow (2010). The masking release appeared to increase as the masker intelligibility decreased. However, it could not be ruled out that spectral differences between the speech maskers were influencing the significant differences observed. Purpose The purpose of the current experiment was to minimize spectral differences between speech maskers to determine how various amounts of linguistic information within competing speech affect masking release. Research Design A mixed model design with within- (four two-talker speech maskers) and between-subject (listener group) factors was conducted. Speech maskers included native-accented English speech, and high-intelligibility, moderate-intelligibility and low-intelligibility Mandarin-accented English. Normalizing the long-term average speech spectra of the maskers to each other minimized spectral differences between the masker conditions. Study Sample Three listener groups were tested including monolingual English speakers with normal hearing, non-native speakers of English with normal hearing, and monolingual speakers of English with hearing loss. The non-native speakers of English were from various native-language backgrounds, not including Mandarin (or any other Chinese dialect). Listeners with hearing loss had symmetrical, mild sloping to moderate sensorineural hearing loss. Data Collection and Analysis Listeners were asked to repeat back sentences that were presented in the presence of four different two-talker speech maskers. Responses were scored based on the keywords within the sentences (100 keywords/masker condition). A mixed-model regression analysis was used to analyze the difference in performance scores between the masker conditions and the listener groups. Results Monolingual speakers of English with normal hearing benefited when the competing speech signal was foreign-accented compared to native-accented allowing for improved speech recognition. Various levels of intelligibility across the foreign-accented speech maskers did not influence results. Neither the non-native English listeners with normal hearing, nor the monolingual English speakers with hearing loss benefited from masking release when the masker was changed from native-accented to foreign-accented English. Conclusions Slight modifications between the target and the masker speech allowed monolingual speakers of English with normal hearing to improve their recognition of native-accented English even when the competing speech was highly intelligible. Further research is needed to determine which modifications within the competing speech signal caused the Mandarin-accented English to be less effective with respect to masking. Determining the influences within the competing speech that make it less effective as a masker, or determining why monolingual normal-hearing listeners can take advantage of these differences could help improve speech recognition for those with hearing loss in the future. PMID:25126683

Deterioration of Speech Recognition Ability Over a Period of 5 Years in Adults Ages 18 to 70 Years: Results of the Dutch Online Speech-in-Noise Test.

PubMed

Stam, Mariska; Smits, Cas; Twisk, Jos W R; Lemke, Ulrike; Festen, Joost M; Kramer, Sophia E

2015-01-01

The first aim of the present study was to determine the change in speech recognition in noise over a period of 5 years in participants ages 18 to 70 years at baseline. The second aim was to investigate whether age, gender, educational level, the level of initial speech recognition in noise, and reported chronic conditions were associated with a change in speech recognition in noise. The baseline and 5-year follow-up data of 427 participants with and without hearing impairment participating in the National Longitudinal Study on Hearing (NL-SH) were analyzed. The ability to recognize speech in noise was measured twice with the online National Hearing Test, a digit-triplet speech-in-noise test. Speech-reception-threshold in noise (SRTn) scores were calculated, corresponding to 50% speech intelligibility. Unaided SRTn scores obtained with the same transducer (headphones or loudspeakers) at both test moments were included. Changes in SRTn were calculated as a raw shift (T1 - T0) and an adjusted shift for regression towards the mean. Paired t tests and multivariable linear regression analyses were applied. The mean increase (i.e., deterioration) in SRTn was 0.38-dB signal-to-noise ratio (SNR) over 5 years (p < 0.001). Results of the multivariable regression analyses showed that the age group of 50 to 59 years had a significantly larger deterioration in SRTn compared with the age group of 18 to 39 years (raw shift: beta: 0.64-dB SNR; 95% confidence interval: 0.07-1.22; p = 0.028, adjusted for initial speech recognition level - adjusted shift: beta: 0.82-dB SNR; 95% confidence interval: 0.27-1.34; p = 0.004). Gender, educational level, and the number of chronic conditions were not associated with a change in SRTn over time. No significant differences in increase of SRTn were found between the initial levels of speech recognition (i.e., good, insufficient, or poor) when taking into account the phenomenon regression towards the mean. The study results indicate that hearing deterioration of speech recognition in noise over 5 years can also be detected in adults ages 18 to 70 years. This rather small numeric change might represent a relevant impact on an individual's ability to understand speech in everyday life.

Enhancing speech recognition using improved particle swarm optimization based hidden Markov model.

PubMed

Selvaraj, Lokesh; Ganesan, Balakrishnan

2014-01-01

Enhancing speech recognition is the primary intention of this work. In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. The suggested methodology contains four stages, namely, (i) denoising, (ii) feature mining (iii), vector quantization, and (iv) IPSO based hidden Markov model (HMM) technique (IP-HMM). At first, the speech signals are denoised using median filter. Next, characteristics such as peak, pitch spectrum, Mel frequency Cepstral coefficients (MFCC), mean, standard deviation, and minimum and maximum of the signal are extorted from the denoised signal. Following that, to accomplish the training process, the extracted characteristics are given to genetic algorithm based codebook generation in vector quantization. The initial populations are created by selecting random code vectors from the training set for the codebooks for the genetic algorithm process and IP-HMM helps in doing the recognition. At this point the creativeness will be done in terms of one of the genetic operation crossovers. The proposed speech recognition technique offers 97.14% accuracy.

A speech-controlled environmental control system for people with severe dysarthria.

PubMed

Hawley, Mark S; Enderby, Pam; Green, Phil; Cunningham, Stuart; Brownsell, Simon; Carmichael, James; Parker, Mark; Hatzis, Athanassios; O'Neill, Peter; Palmer, Rebecca

2007-06-01

Automatic speech recognition (ASR) can provide a rapid means of controlling electronic assistive technology. Off-the-shelf ASR systems function poorly for users with severe dysarthria because of the increased variability of their articulations. We have developed a limited vocabulary speaker dependent speech recognition application which has greater tolerance to variability of speech, coupled with a computerised training package which assists dysarthric speakers to improve the consistency of their vocalisations and provides more data for recogniser training. These applications, and their implementation as the interface for a speech-controlled environmental control system (ECS), are described. The results of field trials to evaluate the training program and the speech-controlled ECS are presented. The user-training phase increased the recognition rate from 88.5% to 95.4% (p<0.001). Recognition rates were good for people with even the most severe dysarthria in everyday usage in the home (mean word recognition rate 86.9%). Speech-controlled ECS were less accurate (mean task completion accuracy 78.6% versus 94.8%) but were faster to use than switch-scanning systems, even taking into account the need to repeat unsuccessful operations (mean task completion time 7.7s versus 16.9s, p<0.001). It is concluded that a speech-controlled ECS is a viable alternative to switch-scanning systems for some people with severe dysarthria and would lead, in many cases, to more efficient control of the home.

Improving speech-in-noise recognition for children with hearing loss: Potential effects of language abilities, binaural summation, and head shadow

PubMed Central

Nittrouer, Susan; Caldwell-Tarr, Amanda; Tarr, Eric; Lowenstein, Joanna H.; Rice, Caitlin; Moberly, Aaron C.

2014-01-01

Objective: This study examined speech recognition in noise for children with hearing loss, compared it to recognition for children with normal hearing, and examined mechanisms that might explain variance in children’s abilities to recognize speech in noise. Design: Word recognition was measured in two levels of noise, both when the speech and noise were co-located in front and when the noise came separately from one side. Four mechanisms were examined as factors possibly explaining variance: vocabulary knowledge, sensitivity to phonological structure, binaural summation, and head shadow. Study sample: Participants were 113 eight-year-old children. Forty-eight had normal hearing (NH) and 65 had hearing loss: 18 with hearing aids (HAs), 19 with one cochlear implant (CI), and 28 with two CIs. Results: Phonological sensitivity explained a significant amount of between-groups variance in speech-in-noise recognition. Little evidence of binaural summation was found. Head shadow was similar in magnitude for children with NH and with CIs, regardless of whether they wore one or two CIs. Children with HAs showed reduced head shadow effects. Conclusion: These outcomes suggest that in order to improve speech-in-noise recognition for children with hearing loss, intervention needs to be comprehensive, focusing on both language abilities and auditory mechanisms. PMID:23834373

Auditory training of speech recognition with interrupted and continuous noise maskers by children with hearing impairment

PubMed Central

Sullivan, Jessica R.; Thibodeau, Linda M.; Assmann, Peter F.

2013-01-01

Previous studies have indicated that individuals with normal hearing (NH) experience a perceptual advantage for speech recognition in interrupted noise compared to continuous noise. In contrast, adults with hearing impairment (HI) and younger children with NH receive a minimal benefit. The objective of this investigation was to assess whether auditory training in interrupted noise would improve speech recognition in noise for children with HI and perhaps enhance their utilization of glimpsing skills. A partially-repeated measures design was used to evaluate the effectiveness of seven 1-h sessions of auditory training in interrupted and continuous noise. Speech recognition scores in interrupted and continuous noise were obtained from pre-, post-, and 3 months post-training from 24 children with moderate-to-severe hearing loss. Children who participated in auditory training in interrupted noise demonstrated a significantly greater improvement in speech recognition compared to those who trained in continuous noise. Those who trained in interrupted noise demonstrated similar improvements in both noise conditions while those who trained in continuous noise only showed modest improvements in the interrupted noise condition. This study presents direct evidence that auditory training in interrupted noise can be beneficial in improving speech recognition in noise for children with HI. PMID:23297921

Segment-based acoustic models for continuous speech recognition

NASA Astrophysics Data System (ADS)

Ostendorf, Mari; Rohlicek, J. R.

1993-07-01

This research aims to develop new and more accurate stochastic models for speaker-independent continuous speech recognition, by extending previous work in segment-based modeling and by introducing a new hierarchical approach to representing intra-utterance statistical dependencies. These techniques, which are more costly than traditional approaches because of the large search space associated with higher order models, are made feasible through rescoring a set of HMM-generated N-best sentence hypotheses. We expect these different modeling techniques to result in improved recognition performance over that achieved by current systems, which handle only frame-based observations and assume that these observations are independent given an underlying state sequence. In the fourth quarter of the project, we have completed the following: (1) ported our recognition system to the Wall Street Journal task, a standard task in the ARPA community; (2) developed an initial dependency-tree model of intra-utterance observation correlation; and (3) implemented baseline language model estimation software. Our initial results on the Wall Street Journal task are quite good and represent significantly improved performance over most HMM systems reporting on the Nov. 1992 5k vocabulary test set.

Relation between measures of speech-in-noise performance and measures of efferent activity

NASA Astrophysics Data System (ADS)

Smith, Brad; Harkrider, Ashley; Burchfield, Samuel; Nabelek, Anna

2003-04-01

Individual differences in auditory perceptual abilities in noise are well documented but the factors causing such variability are unclear. The purpose of this study was to determine if individual differences in responses measured from the auditory efferent system were correlated to individual variations in speech-in-noise performance. The relation between behavioral performance on three speech-in-noise tasks and two objective measures of the efferent auditory system were examined in thirty normal-hearing, young adults. Two of the speech-in-noise tasks measured an acceptable noise level, the maximum level of speech-babble noise that a subject is willing to accept while listening to a story. For these, the acceptable noise level was evaluated using both an ipsilateral (story and noise in same ear) and a contralateral (story and noise in opposite ears) paradigm. The third speech-in-noise task evaluated speech recognition using monosyllabic words presented in competing speech babble. Auditory efferent activity was assessed by examining the resulting suppression of click-evoked otoacoustic emissions following the introduction of a contralateral, broad-band stimulus and the activity of the ipsilateral and contralateral acoustic reflex arc was evaluated using tones and broad-band noise. Results will be discussed relative to current theories of speech in noise performance and auditory inhibitory processes.

Real-Time Reconfigurable Adaptive Speech Recognition Command and Control Apparatus and Method

NASA Technical Reports Server (NTRS)

Salazar, George A. (Inventor); Haynes, Dena S. (Inventor); Sommers, Marc J. (Inventor)

1998-01-01

An adaptive speech recognition and control system and method for controlling various mechanisms and systems in response to spoken instructions and in which spoken commands are effective to direct the system into appropriate memory nodes, and to respective appropriate memory templates corresponding to the voiced command is discussed. Spoken commands from any of a group of operators for which the system is trained may be identified, and voice templates are updated as required in response to changes in pronunciation and voice characteristics over time of any of the operators for which the system is trained. Provisions are made for both near-real-time retraining of the system with respect to individual terms which are determined not be positively identified, and for an overall system training and updating process in which recognition of each command and vocabulary term is checked, and in which the memory templates are retrained if necessary for respective commands or vocabulary terms with respect to an operator currently using the system. In one embodiment, the system includes input circuitry connected to a microphone and including signal processing and control sections for sensing the level of vocabulary recognition over a given period and, if recognition performance falls below a given level, processing audio-derived signals for enhancing recognition performance of the system.

Auditory Outcomes with Hearing Rehabilitation in Children with Unilateral Hearing Loss: A Systematic Review.

PubMed

Appachi, Swathi; Specht, Jessica L; Raol, Nikhila; Lieu, Judith E C; Cohen, Michael S; Dedhia, Kavita; Anne, Samantha

2017-10-01

Objective Options for management of unilateral hearing loss (UHL) in children include conventional hearing aids, bone-conduction hearing devices, contralateral routing of signal (CROS) aids, and frequency-modulating (FM) systems. The objective of this study was to systematically review the current literature to characterize auditory outcomes of hearing rehabilitation options in UHL. Data Sources PubMed, EMBASE, Medline, CINAHL, and Cochrane Library were searched from inception to January 2016. Manual searches of bibliographies were also performed. Review Methods Studies analyzing auditory outcomes of hearing amplification in children with UHL were included. Outcome measures included functional and objective auditory results. Two independent reviewers evaluated each abstract and article. Results Of the 249 articles identified, 12 met inclusion criteria. Seven articles solely focused on outcomes with bone-conduction hearing devices. Outcomes favored improved pure-tone averages, speech recognition thresholds, and sound localization in implanted patients. Five studies focused on FM systems, conventional hearing aids, or CROS hearing aids. Limited data are available but suggest a trend toward improvement in speech perception with hearing aids. FM systems were shown to have the most benefit for speech recognition in noise. Studies evaluating CROS hearing aids demonstrated variable outcomes. Conclusions Data evaluating functional and objective auditory measures following hearing amplification in children with UHL are limited. Most studies do suggest improvement in speech perception, speech recognition in noise, and sound localization with a hearing rehabilitation device.

Investigation of an HMM/ANN hybrid structure in pattern recognition application using cepstral analysis of dysarthric (distorted) speech signals.

PubMed

Polur, Prasad D; Miller, Gerald E

2006-10-01

Computer speech recognition of individuals with dysarthria, such as cerebral palsy patients requires a robust technique that can handle conditions of very high variability and limited training data. In this study, application of a 10 state ergodic hidden Markov model (HMM)/artificial neural network (ANN) hybrid structure for a dysarthric speech (isolated word) recognition system, intended to act as an assistive tool, was investigated. A small size vocabulary spoken by three cerebral palsy subjects was chosen. The effect of such a structure on the recognition rate of the system was investigated by comparing it with an ergodic hidden Markov model as a control tool. This was done in order to determine if this modified technique contributed to enhanced recognition of dysarthric speech. The speech was sampled at 11 kHz. Mel frequency cepstral coefficients were extracted from them using 15 ms frames and served as training input to the hybrid model setup. The subsequent results demonstrated that the hybrid model structure was quite robust in its ability to handle the large variability and non-conformity of dysarthric speech. The level of variability in input dysarthric speech patterns sometimes limits the reliability of the system. However, its application as a rehabilitation/control tool to assist dysarthric motor impaired individuals holds sufficient promise.

Effects of intelligibility on working memory demand for speech perception.

PubMed

Francis, Alexander L; Nusbaum, Howard C

2009-08-01

Understanding low-intelligibility speech is effortful. In three experiments, we examined the effects of intelligibility on working memory (WM) demands imposed by perception of synthetic speech. In all three experiments, a primary speeded word recognition task was paired with a secondary WM-load task designed to vary the availability of WM capacity during speech perception. Speech intelligibility was varied either by training listeners to use available acoustic cues in a more diagnostic manner (as in Experiment 1) or by providing listeners with more informative acoustic cues (i.e., better speech quality, as in Experiments 2 and 3). In the first experiment, training significantly improved intelligibility and recognition speed; increasing WM load significantly slowed recognition. A significant interaction between training and load indicated that the benefit of training on recognition speed was observed only under low memory load. In subsequent experiments, listeners received no training; intelligibility was manipulated by changing synthesizers. Improving intelligibility without training improved recognition accuracy, and increasing memory load still decreased it, but more intelligible speech did not produce more efficient use of available WM capacity. This suggests that perceptual learning modifies the way available capacity is used, perhaps by increasing the use of more phonetically informative features and/or by decreasing use of less informative ones.

Self-Assessed Hearing Handicap in Older Adults With Poorer-Than-Predicted Speech Recognition in Noise.

PubMed

Eckert, Mark A; Matthews, Lois J; Dubno, Judy R

2017-01-01

Even older adults with relatively mild hearing loss report hearing handicap, suggesting that hearing handicap is not completely explained by reduced speech audibility. We examined the extent to which self-assessed ratings of hearing handicap using the Hearing Handicap Inventory for the Elderly (HHIE; Ventry & Weinstein, 1982) were significantly associated with measures of speech recognition in noise that controlled for differences in speech audibility. One hundred sixty-two middle-aged and older adults had HHIE total scores that were significantly associated with audibility-adjusted measures of speech recognition for low-context but not high-context sentences. These findings were driven by HHIE items involving negative feelings related to communication difficulties that also captured variance in subjective ratings of effort and frustration that predicted speech recognition. The average pure-tone threshold accounted for some of the variance in the association between the HHIE and audibility-adjusted speech recognition, suggesting an effect of central and peripheral auditory system decline related to elevated thresholds. The accumulation of difficult listening experiences appears to produce a self-assessment of hearing handicap resulting from (a) reduced audibility of stimuli, (b) declines in the central and peripheral auditory system function, and (c) additional individual variation in central nervous system function.

Self-Assessed Hearing Handicap in Older Adults With Poorer-Than-Predicted Speech Recognition in Noise

PubMed Central

Matthews, Lois J.; Dubno, Judy R.

2017-01-01

Purpose Even older adults with relatively mild hearing loss report hearing handicap, suggesting that hearing handicap is not completely explained by reduced speech audibility. Method We examined the extent to which self-assessed ratings of hearing handicap using the Hearing Handicap Inventory for the Elderly (HHIE; Ventry & Weinstein, 1982) were significantly associated with measures of speech recognition in noise that controlled for differences in speech audibility. Results One hundred sixty-two middle-aged and older adults had HHIE total scores that were significantly associated with audibility-adjusted measures of speech recognition for low-context but not high-context sentences. These findings were driven by HHIE items involving negative feelings related to communication difficulties that also captured variance in subjective ratings of effort and frustration that predicted speech recognition. The average pure-tone threshold accounted for some of the variance in the association between the HHIE and audibility-adjusted speech recognition, suggesting an effect of central and peripheral auditory system decline related to elevated thresholds. Conclusion The accumulation of difficult listening experiences appears to produce a self-assessment of hearing handicap resulting from (a) reduced audibility of stimuli, (b) declines in the central and peripheral auditory system function, and (c) additional individual variation in central nervous system function. PMID:28060993

Double Fourier analysis for Emotion Identification in Voiced Speech

NASA Astrophysics Data System (ADS)

Sierra-Sosa, D.; Bastidas, M.; Ortiz P., D.; Quintero, O. L.

2016-04-01

We propose a novel analysis alternative, based on two Fourier Transforms for emotion recognition from speech. Fourier analysis allows for display and synthesizes different signals, in terms of power spectral density distributions. A spectrogram of the voice signal is obtained performing a short time Fourier Transform with Gaussian windows, this spectrogram portraits frequency related features, such as vocal tract resonances and quasi-periodic excitations during voiced sounds. Emotions induce such characteristics in speech, which become apparent in spectrogram time-frequency distributions. Later, the signal time-frequency representation from spectrogram is considered an image, and processed through a 2-dimensional Fourier Transform in order to perform the spatial Fourier analysis from it. Finally features related with emotions in voiced speech are extracted and presented.

Robust audio-visual speech recognition under noisy audio-video conditions.

PubMed

Stewart, Darryl; Seymour, Rowan; Pass, Adrian; Ming, Ji

2014-02-01

This paper presents the maximum weighted stream posterior (MWSP) model as a robust and efficient stream integration method for audio-visual speech recognition in environments, where the audio or video streams may be subjected to unknown and time-varying corruption. A significant advantage of MWSP is that it does not require any specific measurements of the signal in either stream to calculate appropriate stream weights during recognition, and as such it is modality-independent. This also means that MWSP complements and can be used alongside many of the other approaches that have been proposed in the literature for this problem. For evaluation we used the large XM2VTS database for speaker-independent audio-visual speech recognition. The extensive tests include both clean and corrupted utterances with corruption added in either/both the video and audio streams using a variety of types (e.g., MPEG-4 video compression) and levels of noise. The experiments show that this approach gives excellent performance in comparison to another well-known dynamic stream weighting approach and also compared to any fixed-weighted integration approach in both clean conditions or when noise is added to either stream. Furthermore, our experiments show that the MWSP approach dynamically selects suitable integration weights on a frame-by-frame basis according to the level of noise in the streams and also according to the naturally fluctuating relative reliability of the modalities even in clean conditions. The MWSP approach is shown to maintain robust recognition performance in all tested conditions, while requiring no prior knowledge about the type or level of noise.

Integrated voice and visual systems research topics

NASA Technical Reports Server (NTRS)

Williams, Douglas H.; Simpson, Carol A.

1986-01-01

A series of studies was performed to investigate factors of helicopter speech and visual system design and measure the effects of these factors on human performance, both for pilots and non-pilots. The findings and conclusions of these studies were applied by the U.S. Army to the design of the Army's next generation threat warning system for helicopters and to the linguistic functional requirements for a joint Army/NASA flightworthy, experimental speech generation and recognition system.

Speech recognition: Acoustic phonetic and lexical knowledge representation

NASA Astrophysics Data System (ADS)

Zue, V. W.

1983-02-01

The purpose of this program is to develop a speech data base facility under which the acoustic characteristics of speech sounds in various contexts can be studied conveniently; investigate the phonological properties of a large lexicon of, say 10,000 words, and determine to what extent the phontactic constraints can be utilized in speech recognition; study the acoustic cues that are used to mark work boundaries; develop a test bed in the form of a large-vocabulary, IWR system to study the interactions of acoustic, phonetic and lexical knowledge; and develop a limited continuous speech recognition system with the goal of recognizing any English word from its spelling in order to assess the interactions of higher-level knowledge sources.

Integration of Speech and Natural Language

DTIC Science & Technology

1988-04-01

major activities: • Development of the syntax and semantics components for natural language processing. • Integration of the developed syntax and...evaluating the performance of speech recognition algonthms developed K» under the Strategic Computing Program. grs Our work on natural language processing...included the developement of a grammar (syntax) that uses the Uiuficanon gnmmaj formaMsm (an augmented context free formalism). The Unification

Masking release due to linguistic and phonetic dissimilarity between the target and masker speech

PubMed Central

Calandruccio, Lauren; Brouwer, Susanne; Van Engen, Kristin J.; Dhar, Sumitrajit; Bradlow, Ann R.

2013-01-01

Purpose To investigate masking release for speech maskers for linguistically and phonetically close (English and Dutch) and distant (English and Mandarin) language pairs. Method Twenty monolingual speakers of English with normal-audiometric thresholds participated. Data are reported for an English sentence recognition task in English, Dutch and Mandarin competing speech maskers (Experiment I) and noise maskers (Experiment II) that were matched either to the long-term-average-speech spectra or to the temporal modulations of the speech maskers from Experiment I. Results Results indicated that listener performance increased as the target-to-masker linguistic distance increased (English-in-English < English-in-Dutch < English-in-Mandarin). Conclusions Spectral differences between maskers can account for some, but not all, of the variation in performance between maskers; however, temporal differences did not seem to play a significant role. PMID:23800811

Comparing models of the combined-stimulation advantage for speech recognition.

PubMed

Micheyl, Christophe; Oxenham, Andrew J

2012-05-01

The "combined-stimulation advantage" refers to an improvement in speech recognition when cochlear-implant or vocoded stimulation is supplemented by low-frequency acoustic information. Previous studies have been interpreted as evidence for "super-additive" or "synergistic" effects in the combination of low-frequency and electric or vocoded speech information by human listeners. However, this conclusion was based on predictions of performance obtained using a suboptimal high-threshold model of information combination. The present study shows that a different model, based on Gaussian signal detection theory, can predict surprisingly large combined-stimulation advantages, even when performance with either information source alone is close to chance, without involving any synergistic interaction. A reanalysis of published data using this model reveals that previous results, which have been interpreted as evidence for super-additive effects in perception of combined speech stimuli, are actually consistent with a more parsimonious explanation, according to which the combined-stimulation advantage reflects an optimal combination of two independent sources of information. The present results do not rule out the possible existence of synergistic effects in combined stimulation; however, they emphasize the possibility that the combined-stimulation advantages observed in some studies can be explained simply by non-interactive combination of two information sources.

Speech to Text Translation for Malay Language

NASA Astrophysics Data System (ADS)

Al-khulaidi, Rami Ali; Akmeliawati, Rini

2017-11-01

The speech recognition system is a front end and a back-end process that receives an audio signal uttered by a speaker and converts it into a text transcription. The speech system can be used in several fields including: therapeutic technology, education, social robotics and computer entertainments. In most cases in control tasks, which is the purpose of proposing our system, wherein the speed of performance and response concern as the system should integrate with other controlling platforms such as in voiced controlled robots. Therefore, the need for flexible platforms, that can be easily edited to jibe with functionality of the surroundings, came to the scene; unlike other software programs that require recording audios and multiple training for every entry such as MATLAB and Phoenix. In this paper, a speech recognition system for Malay language is implemented using Microsoft Visual Studio C#. 90 (ninety) Malay phrases were tested by 10 (ten) speakers from both genders in different contexts. The result shows that the overall accuracy (calculated from Confusion Matrix) is satisfactory as it is 92.69%.

Functional Connectivity between Face-Movement and Speech-Intelligibility Areas during Auditory-Only Speech Perception

PubMed Central

Schall, Sonja; von Kriegstein, Katharina

2014-01-01

It has been proposed that internal simulation of the talking face of visually-known speakers facilitates auditory speech recognition. One prediction of this view is that brain areas involved in auditory-only speech comprehension interact with visual face-movement sensitive areas, even under auditory-only listening conditions. Here, we test this hypothesis using connectivity analyses of functional magnetic resonance imaging (fMRI) data. Participants (17 normal participants, 17 developmental prosopagnosics) first learned six speakers via brief voice-face or voice-occupation training (<2 min/speaker). This was followed by an auditory-only speech recognition task and a control task (voice recognition) involving the learned speakers’ voices in the MRI scanner. As hypothesized, we found that, during speech recognition, familiarity with the speaker’s face increased the functional connectivity between the face-movement sensitive posterior superior temporal sulcus (STS) and an anterior STS region that supports auditory speech intelligibility. There was no difference between normal participants and prosopagnosics. This was expected because previous findings have shown that both groups use the face-movement sensitive STS to optimize auditory-only speech comprehension. Overall, the present findings indicate that learned visual information is integrated into the analysis of auditory-only speech and that this integration results from the interaction of task-relevant face-movement and auditory speech-sensitive areas. PMID:24466026

A preliminary comparison of speech recognition functionality in dental practice management systems.

PubMed

Irwin, Jeannie Y; Schleyer, Titus

2008-11-06

In this study, we examined speech recognition functionality in four leading dental practice management systems. Twenty dental students used voice to chart a simulated patient with 18 findings in each system. Results show it can take over a minute to chart one finding and that users frequently have to repeat commands. Limited functionality, poor usability and a high error rate appear to retard adoption of speech recognition in dentistry.

Two Stage Data Augmentation for Low Resourced Speech Recognition (Author’s Manuscript)

DTIC Science & Technology

2016-09-12

speech recognition, deep neural networks, data augmentation 1. Introduction When training data is limited—whether it be audio or text—the obvious...Schwartz, and S. Tsakalidis, “Enhancing low resource keyword spotting with au- tomatically retrieved web documents,” in Interspeech, 2015, pp. 839–843. [2...and F. Seide, “Feature learning in deep neural networks - a study on speech recognition tasks,” in International Conference on Learning Representations

Getting What You Want: Accurate Document Filtering in a Terabyte World

DTIC Science & Technology

2002-11-01

models are used widely in speech recognition and have shown promise for ad-hoc information retrieval (Ponte and Croft, 1998; Lafferty and Zhai, 2001...tasks is focused on developing techniques similar to those used in speech recognition. However the differing requirements of speech recognition and...Conference on Research and Development in Information Retrieval. ACM. 6. T.Ault, and Y. Yang. (2001.) kNN at TREC-9: A failure analysis. In

Development and preliminary evaluation of a pediatric Spanish-English speech perception task.

PubMed

Calandruccio, Lauren; Gomez, Bianca; Buss, Emily; Leibold, Lori J

2014-06-01

The purpose of this study was to develop a task to evaluate children's English and Spanish speech perception abilities in either noise or competing speech maskers. Eight bilingual Spanish-English and 8 age-matched monolingual English children (ages 4.9-16.4 years) were tested. A forced-choice, picture-pointing paradigm was selected for adaptively estimating masked speech reception thresholds. Speech stimuli were spoken by simultaneous bilingual Spanish-English talkers. The target stimuli were 30 disyllabic English and Spanish words, familiar to 5-year-olds and easily illustrated. Competing stimuli included either 2-talker English or 2-talker Spanish speech (corresponding to target language) and spectrally matched noise. For both groups of children, regardless of test language, performance was significantly worse for the 2-talker than for the noise masker condition. No difference in performance was found between bilingual and monolingual children. Bilingual children performed significantly better in English than in Spanish in competing speech. For all listening conditions, performance improved with increasing age. Results indicated that the stimuli and task were appropriate for speech recognition testing in both languages, providing a more conventional measure of speech-in-noise perception as well as a measure of complex listening. Further research is needed to determine performance for Spanish-dominant listeners and to evaluate the feasibility of implementation into routine clinical use.

Development and preliminary evaluation of a pediatric Spanish/English speech perception task

PubMed Central

Calandruccio, Lauren; Gomez, Bianca; Buss, Emily; Leibold, Lori J.

2014-01-01

Purpose To develop a task to evaluate children’s English and Spanish speech perception abilities in either noise or competing speech maskers. Methods Eight bilingual Spanish/English and eight age matched monolingual English children (ages 4.9 –16.4 years) were tested. A forced-choice, picture-pointing paradigm was selected for adaptively estimating masked speech reception thresholds. Speech stimuli were spoken by simultaneous bilingual Spanish/English talkers. The target stimuli were thirty disyllabic English and Spanish words, familiar to five-year-olds, and easily illustrated. Competing stimuli included either two-talker English or two-talker Spanish speech (corresponding to target language) and spectrally matched noise. Results For both groups of children, regardless of test language, performance was significantly worse for the two-talker than the noise masker. No difference in performance was found between bilingual and monolingual children. Bilingual children performed significantly better in English than in Spanish in competing speech. For all listening conditions, performance improved with increasing age. Conclusions Results indicate that the stimuli and task are appropriate for speech recognition testing in both languages, providing a more conventional measure of speech-in-noise perception as well as a measure of complex listening. Further research is needed to determine performance for Spanish-dominant listeners and to evaluate the feasibility of implementation into routine clinical use. PMID:24686915

Right anterior superior temporal activation predicts auditory sentence comprehension following aphasic stroke.

PubMed

Crinion, Jenny; Price, Cathy J

2005-12-01

Previous studies have suggested that recovery of speech comprehension after left hemisphere infarction may depend on a mechanism in the right hemisphere. However, the role that distinct right hemisphere regions play in speech comprehension following left hemisphere stroke has not been established. Here, we used functional magnetic resonance imaging (fMRI) to investigate narrative speech activation in 18 neurologically normal subjects and 17 patients with left hemisphere stroke and a history of aphasia. Activation for listening to meaningful stories relative to meaningless reversed speech was identified in the normal subjects and in each patient. Second level analyses were then used to investigate how story activation changed with the patients' auditory sentence comprehension skills and surprise story recognition memory tests post-scanning. Irrespective of lesion site, performance on tests of auditory sentence comprehension was positively correlated with activation in the right lateral superior temporal region, anterior to primary auditory cortex. In addition, when the stroke spared the left temporal cortex, good performance on tests of auditory sentence comprehension was also correlated with the left posterior superior temporal cortex (Wernicke's area). In distinct contrast to this, good story recognition memory predicted left inferior frontal and right cerebellar activation. The implication of this double dissociation in the effects of auditory sentence comprehension and story recognition memory is that left frontal and left temporal activations are dissociable. Our findings strongly support the role of the right temporal lobe in processing narrative speech and, in particular, auditory sentence comprehension following left hemisphere aphasic stroke. In addition, they highlight the importance of the right anterior superior temporal cortex where the response was dissociated from that in the left posterior temporal lobe.

Linguistic contributions to speech-on-speech masking for native and non-native listeners: language familiarity and semantic content.

PubMed

Brouwer, Susanne; Van Engen, Kristin J; Calandruccio, Lauren; Bradlow, Ann R

2012-02-01

This study examined whether speech-on-speech masking is sensitive to variation in the degree of similarity between the target and the masker speech. Three experiments investigated whether speech-in-speech recognition varies across different background speech languages (English vs Dutch) for both English and Dutch targets, as well as across variation in the semantic content of the background speech (meaningful vs semantically anomalous sentences), and across variation in listener status vis-à-vis the target and masker languages (native, non-native, or unfamiliar). The results showed that the more similar the target speech is to the masker speech (e.g., same vs different language, same vs different levels of semantic content), the greater the interference on speech recognition accuracy. Moreover, the listener's knowledge of the target and the background language modulate the size of the release from masking. These factors had an especially strong effect on masking effectiveness in highly unfavorable listening conditions. Overall this research provided evidence that that the degree of target-masker similarity plays a significant role in speech-in-speech recognition. The results also give insight into how listeners assign their resources differently depending on whether they are listening to their first or second language. © 2012 Acoustical Society of America

Linguistic contributions to speech-on-speech masking for native and non-native listeners: Language familiarity and semantic content

PubMed Central

Brouwer, Susanne; Van Engen, Kristin J.; Calandruccio, Lauren; Bradlow, Ann R.

2012-01-01

This study examined whether speech-on-speech masking is sensitive to variation in the degree of similarity between the target and the masker speech. Three experiments investigated whether speech-in-speech recognition varies across different background speech languages (English vs Dutch) for both English and Dutch targets, as well as across variation in the semantic content of the background speech (meaningful vs semantically anomalous sentences), and across variation in listener status vis-à-vis the target and masker languages (native, non-native, or unfamiliar). The results showed that the more similar the target speech is to the masker speech (e.g., same vs different language, same vs different levels of semantic content), the greater the interference on speech recognition accuracy. Moreover, the listener’s knowledge of the target and the background language modulate the size of the release from masking. These factors had an especially strong effect on masking effectiveness in highly unfavorable listening conditions. Overall this research provided evidence that that the degree of target-masker similarity plays a significant role in speech-in-speech recognition. The results also give insight into how listeners assign their resources differently depending on whether they are listening to their first or second language. PMID:22352516

Speech Recognition in Adults With Cochlear Implants: The Effects of Working Memory, Phonological Sensitivity, and Aging.

PubMed

Moberly, Aaron C; Harris, Michael S; Boyce, Lauren; Nittrouer, Susan

2017-04-14

Models of speech recognition suggest that "top-down" linguistic and cognitive functions, such as use of phonotactic constraints and working memory, facilitate recognition under conditions of degradation, such as in noise. The question addressed in this study was what happens to these functions when a listener who has experienced years of hearing loss obtains a cochlear implant. Thirty adults with cochlear implants and 30 age-matched controls with age-normal hearing underwent testing of verbal working memory using digit span and serial recall of words. Phonological capacities were assessed using a lexical decision task and nonword repetition. Recognition of words in sentences in speech-shaped noise was measured. Implant users had only slightly poorer working memory accuracy than did controls and only on serial recall of words; however, phonological sensitivity was highly impaired. Working memory did not facilitate speech recognition in noise for either group. Phonological sensitivity predicted sentence recognition for implant users but not for listeners with normal hearing. Clinical speech recognition outcomes for adult implant users relate to the ability of these users to process phonological information. Results suggest that phonological capacities may serve as potential clinical targets through rehabilitative training. Such novel interventions may be particularly helpful for older adult implant users.

Speech Recognition in Adults With Cochlear Implants: The Effects of Working Memory, Phonological Sensitivity, and Aging

PubMed Central

Harris, Michael S.; Boyce, Lauren; Nittrouer, Susan

2017-01-01

Purpose Models of speech recognition suggest that “top-down” linguistic and cognitive functions, such as use of phonotactic constraints and working memory, facilitate recognition under conditions of degradation, such as in noise. The question addressed in this study was what happens to these functions when a listener who has experienced years of hearing loss obtains a cochlear implant. Method Thirty adults with cochlear implants and 30 age-matched controls with age-normal hearing underwent testing of verbal working memory using digit span and serial recall of words. Phonological capacities were assessed using a lexical decision task and nonword repetition. Recognition of words in sentences in speech-shaped noise was measured. Results Implant users had only slightly poorer working memory accuracy than did controls and only on serial recall of words; however, phonological sensitivity was highly impaired. Working memory did not facilitate speech recognition in noise for either group. Phonological sensitivity predicted sentence recognition for implant users but not for listeners with normal hearing. Conclusion Clinical speech recognition outcomes for adult implant users relate to the ability of these users to process phonological information. Results suggest that phonological capacities may serve as potential clinical targets through rehabilitative training. Such novel interventions may be particularly helpful for older adult implant users. PMID:28384805

Speech Recognition Thresholds for Multilingual Populations.

ERIC Educational Resources Information Center

Ramkissoon, Ishara

2001-01-01

This article traces the development of speech audiometry in the United States and reports on the current status, focusing on the needs of a multilingual population in terms of measuring speech recognition threshold (SRT). It also discusses sociolinguistic considerations, alternative SRT stimuli for second language learners, and research on using…

Random Deep Belief Networks for Recognizing Emotions from Speech Signals.

PubMed

Wen, Guihua; Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang

2017-01-01

Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition.

Random Deep Belief Networks for Recognizing Emotions from Speech Signals

PubMed Central

Li, Huihui; Huang, Jubing; Li, Danyang; Xun, Eryang

2017-01-01

Now the human emotions can be recognized from speech signals using machine learning methods; however, they are challenged by the lower recognition accuracies in real applications due to lack of the rich representation ability. Deep belief networks (DBN) can automatically discover the multiple levels of representations in speech signals. To make full of its advantages, this paper presents an ensemble of random deep belief networks (RDBN) method for speech emotion recognition. It firstly extracts the low level features of the input speech signal and then applies them to construct lots of random subspaces. Each random subspace is then provided for DBN to yield the higher level features as the input of the classifier to output an emotion label. All outputted emotion labels are then fused through the majority voting to decide the final emotion label for the input speech signal. The conducted experimental results on benchmark speech emotion databases show that RDBN has better accuracy than the compared methods for speech emotion recognition. PMID:28356908

A Method for Determining the Timing of Displaying the Speaker's Face and Captions for a Real-Time Speech-to-Caption System

NASA Astrophysics Data System (ADS)

Kuroki, Hayato; Ino, Shuichi; Nakano, Satoko; Hori, Kotaro; Ifukube, Tohru

The authors of this paper have been studying a real-time speech-to-caption system using speech recognition technology with a “repeat-speaking” method. In this system, they used a “repeat-speaker” who listens to a lecturer's voice and then speaks back the lecturer's speech utterances into a speech recognition computer. The througoing system showed that the accuracy of the captions is about 97% in Japanese-Japanese conversion and the conversion time from voices to captions is about 4 seconds in English-English conversion in some international conferences. Of course it required a lot of costs to achieve these high performances. In human communications, speech understanding depends not only on verbal information but also on non-verbal information such as speaker's gestures, and face and mouth movements. So the authors found the idea to display information of captions and speaker's face movement images with a suitable way to achieve a higher comprehension after storing information once into a computer briefly. In this paper, we investigate the relationship of the display sequence and display timing between captions that have speech recognition errors and the speaker's face movement images. The results show that the sequence “to display the caption before the speaker's face image” improves the comprehension of the captions. The sequence “to display both simultaneously” shows an improvement only a few percent higher than the question sentence, and the sequence “to display the speaker's face image before the caption” shows almost no change. In addition, the sequence “to display the caption 1 second before the speaker's face shows the most significant improvement of all the conditions.

Speech recognition for embedded automatic positioner for laparoscope

NASA Astrophysics Data System (ADS)

Chen, Xiaodong; Yin, Qingyun; Wang, Yi; Yu, Daoyin

2014-07-01

In this paper a novel speech recognition methodology based on Hidden Markov Model (HMM) is proposed for embedded Automatic Positioner for Laparoscope (APL), which includes a fixed point ARM processor as the core. The APL system is designed to assist the doctor in laparoscopic surgery, by implementing the specific doctor's vocal control to the laparoscope. Real-time respond to the voice commands asks for more efficient speech recognition algorithm for the APL. In order to reduce computation cost without significant loss in recognition accuracy, both arithmetic and algorithmic optimizations are applied in the method presented. First, depending on arithmetic optimizations most, a fixed point frontend for speech feature analysis is built according to the ARM processor's character. Then the fast likelihood computation algorithm is used to reduce computational complexity of the HMM-based recognition algorithm. The experimental results show that, the method shortens the recognition time within 0.5s, while the accuracy higher than 99%, demonstrating its ability to achieve real-time vocal control to the APL.

Spatial release of cognitive load measured in a dual-task paradigm in normal-hearing and hearing-impaired listeners.

PubMed

Xia, Jing; Nooraei, Nazanin; Kalluri, Sridhar; Edwards, Brent

2015-04-01

This study investigated whether spatial separation between talkers helps reduce cognitive processing load, and how hearing impairment interacts with the cognitive load of individuals listening in multi-talker environments. A dual-task paradigm was used in which performance on a secondary task (visual tracking) served as a measure of the cognitive load imposed by a speech recognition task. Visual tracking performance was measured under four conditions in which the target and the interferers were distinguished by (1) gender and spatial location, (2) gender only, (3) spatial location only, and (4) neither gender nor spatial location. Results showed that when gender cues were available, a 15° spatial separation between talkers reduced the cognitive load of listening even though it did not provide further improvement in speech recognition (Experiment I). Compared to normal-hearing listeners, large individual variability in spatial release of cognitive load was observed among hearing-impaired listeners. Cognitive load was lower when talkers were spatially separated by 60° than when talkers were of different genders, even though speech recognition was comparable in these two conditions (Experiment II). These results suggest that a measure of cognitive load might provide valuable insight into the benefit of spatial cues in multi-talker environments.

Recognition of voice commands using adaptation of foreign language speech recognizer via selection of phonetic transcriptions

NASA Astrophysics Data System (ADS)

Maskeliunas, Rytis; Rudzionis, Vytautas

2011-06-01

In recent years various commercial speech recognizers have become available. These recognizers provide the possibility to develop applications incorporating various speech recognition techniques easily and quickly. All of these commercial recognizers are typically targeted to widely spoken languages having large market potential; however, it may be possible to adapt available commercial recognizers for use in environments where less widely spoken languages are used. Since most commercial recognition engines are closed systems the single avenue for the adaptation is to try set ways for the selection of proper phonetic transcription methods between the two languages. This paper deals with the methods to find the phonetic transcriptions for Lithuanian voice commands to be recognized using English speech engines. The experimental evaluation showed that it is possible to find phonetic transcriptions that will enable the recognition of Lithuanian voice commands with recognition accuracy of over 90%.

A cascaded neuro-computational model for spoken word recognition

NASA Astrophysics Data System (ADS)

Hoya, Tetsuya; van Leeuwen, Cees

2010-03-01

In human speech recognition, words are analysed at both pre-lexical (i.e., sub-word) and lexical (word) levels. The aim of this paper is to propose a constructive neuro-computational model that incorporates both these levels as cascaded layers of pre-lexical and lexical units. The layered structure enables the system to handle the variability of real speech input. Within the model, receptive fields of the pre-lexical layer consist of radial basis functions; the lexical layer is composed of units that perform pattern matching between their internal template and a series of labels, corresponding to the winning receptive fields in the pre-lexical layer. The model adapts through self-tuning of all units, in combination with the formation of a connectivity structure through unsupervised (first layer) and supervised (higher layers) network growth. Simulation studies show that the model can achieve a level of performance in spoken word recognition similar to that of a benchmark approach using hidden Markov models, while enabling parallel access to word candidates in lexical decision making.

Schizophrenia affects speech-induced functional connectivity of the superior temporal gyrus under cocktail-party listening conditions.

PubMed

Li, Juanhua; Wu, Chao; Zheng, Yingjun; Li, Ruikeng; Li, Xuanzi; She, Shenglin; Wu, Haibo; Peng, Hongjun; Ning, Yuping; Li, Liang

2017-09-17

The superior temporal gyrus (STG) is involved in speech recognition against informational masking under cocktail-party-listening conditions. Compared to healthy listeners, people with schizophrenia perform worse in speech recognition under informational speech-on-speech masking conditions. It is not clear whether the schizophrenia-related vulnerability to informational masking is associated with certain changes in FC of the STG with some critical brain regions. Using sparse-sampling fMRI design, this study investigated the differences between people with schizophrenia and healthy controls in FC of the STG for target-speech listening against informational speech-on-speech masking, when a listening condition with either perceived spatial separation (PSS, with a spatial release of informational masking) or perceived spatial co-location (PSC, without the spatial release) between target speech and masking speech was introduced. The results showed that in healthy participants, but not participants with schizophrenia, the contrast of either the PSS or PSC condition against the masker-only condition induced an enhancement of functional connectivity (FC) of the STG with the left superior parietal lobule and the right precuneus. Compared to healthy participants, participants with schizophrenia showed declined FC of the STG with the bilateral precuneus, right SPL, and right supplementary motor area. Thus, FC of the STG with the parietal areas is normally involved in speech listening against informational masking under either the PSS or PSC conditions, and declined FC of the STG in people with schizophrenia with the parietal areas may be associated with the increased vulnerability to informational masking. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.

Optimal pattern synthesis for speech recognition based on principal component analysis

NASA Astrophysics Data System (ADS)

Korsun, O. N.; Poliyev, A. V.

2018-02-01

The algorithm for building an optimal pattern for the purpose of automatic speech recognition, which increases the probability of correct recognition, is developed and presented in this work. The optimal pattern forming is based on the decomposition of an initial pattern to principal components, which enables to reduce the dimension of multi-parameter optimization problem. At the next step the training samples are introduced and the optimal estimates for principal components decomposition coefficients are obtained by a numeric parameter optimization algorithm. Finally, we consider the experiment results that show the improvement in speech recognition introduced by the proposed optimization algorithm.

Speaker Recognition by Combining MFCC and Phase Information in Noisy Conditions

NASA Astrophysics Data System (ADS)

Wang, Longbiao; Minami, Kazue; Yamamoto, Kazumasa; Nakagawa, Seiichi

In this paper, we investigate the effectiveness of phase for speaker recognition in noisy conditions and combine the phase information with mel-frequency cepstral coefficients (MFCCs). To date, almost speaker recognition methods are based on MFCCs even in noisy conditions. For MFCCs which dominantly capture vocal tract information, only the magnitude of the Fourier Transform of time-domain speech frames is used and phase information has been ignored. High complement of the phase information and MFCCs is expected because the phase information includes rich voice source information. Furthermore, some researches have reported that phase based feature was robust to noise. In our previous study, a phase information extraction method that normalizes the change variation in the phase depending on the clipping position of the input speech was proposed, and the performance of the combination of the phase information and MFCCs was remarkably better than that of MFCCs. In this paper, we evaluate the robustness of the proposed phase information for speaker identification in noisy conditions. Spectral subtraction, a method skipping frames with low energy/Signal-to-Noise (SN) and noisy speech training models are used to analyze the effect of the phase information and MFCCs in noisy conditions. The NTT database and the JNAS (Japanese Newspaper Article Sentences) database added with stationary/non-stationary noise were used to evaluate our proposed method. MFCCs outperformed the phase information for clean speech. On the other hand, the degradation of the phase information was significantly smaller than that of MFCCs for noisy speech. The individual result of the phase information was even better than that of MFCCs in many cases by clean speech training models. By deleting unreliable frames (frames having low energy/SN), the speaker identification performance was improved significantly. By integrating the phase information with MFCCs, the speaker identification error reduction rate was about 30%-60% compared with the standard MFCC-based method.

Art critic: Multisignal vision and speech interaction system in a gaming context.

PubMed

Reale, Michael J; Liu, Peng; Yin, Lijun; Canavan, Shaun

2013-12-01

True immersion of a player within a game can only occur when the world simulated looks and behaves as close to reality as possible. This implies that the game must correctly read and understand, among other things, the player's focus, attitude toward the objects/persons in focus, gestures, and speech. In this paper, we proposed a novel system that integrates eye gaze estimation, head pose estimation, facial expression recognition, speech recognition, and text-to-speech components for use in real-time games. Both the eye gaze and head pose components utilize underlying 3-D models, and our novel head pose estimation algorithm uniquely combines scene flow with a generic head model. The facial expression recognition module uses the local binary patterns with three orthogonal planes approach on the 2-D shape index domain rather than the pixel domain, resulting in improved classification. Our system has also been extended to use a pan-tilt-zoom camera driven by the Kinect, allowing us to track a moving player. A test game, Art Critic, is also presented, which not only demonstrates the utility of our system but also provides a template for player/non-player character (NPC) interaction in a gaming context. The player alters his/her view of the 3-D world using head pose, looks at paintings/NPCs using eye gaze, and makes an evaluation based on the player's expression and speech. The NPC artist will respond with facial expression and synthetic speech based on its personality. Both qualitative and quantitative evaluations of the system are performed to illustrate the system's effectiveness.

ERP evidence for the recognition of emotional prosody through simulated cochlear implant strategies.

PubMed

Agrawal, Deepashri; Timm, Lydia; Viola, Filipa Campos; Debener, Stefan; Büchner, Andreas; Dengler, Reinhard; Wittfoth, Matthias

2012-09-20

Emotionally salient information in spoken language can be provided by variations in speech melody (prosody) or by emotional semantics. Emotional prosody is essential to convey feelings through speech. In sensori-neural hearing loss, impaired speech perception can be improved by cochlear implants (CIs). Aim of this study was to investigate the performance of normal-hearing (NH) participants on the perception of emotional prosody with vocoded stimuli. Semantically neutral sentences with emotional (happy, angry and neutral) prosody were used. Sentences were manipulated to simulate two CI speech-coding strategies: the Advance Combination Encoder (ACE) and the newly developed Psychoacoustic Advanced Combination Encoder (PACE). Twenty NH adults were asked to recognize emotional prosody from ACE and PACE simulations. Performance was assessed using behavioral tests and event-related potentials (ERPs). Behavioral data revealed superior performance with original stimuli compared to the simulations. For simulations, better recognition for happy and angry prosody was observed compared to the neutral. Irrespective of simulated or unsimulated stimulus type, a significantly larger P200 event-related potential was observed for happy prosody after sentence onset than the other two emotions. Further, the amplitude of P200 was significantly more positive for PACE strategy use compared to the ACE strategy. Results suggested P200 peak as an indicator of active differentiation and recognition of emotional prosody. Larger P200 peak amplitude for happy prosody indicated importance of fundamental frequency (F0) cues in prosody processing. Advantage of PACE over ACE highlighted a privileged role of the psychoacoustic masking model in improving prosody perception. Taken together, the study emphasizes on the importance of vocoded simulation to better understand the prosodic cues which CI users may be utilizing.

Development and validation of a smartphone-based digits-in-noise hearing test in South African English.

PubMed

Potgieter, Jenni-Marí; Swanepoel, De Wet; Myburgh, Hermanus Carel; Hopper, Thomas Christopher; Smits, Cas

2015-07-01

The objective of this study was to develop and validate a smartphone-based digits-in-noise hearing test for South African English. Single digits (0-9) were recorded and spoken by a first language English female speaker. Level corrections were applied to create a set of homogeneous digits with steep speech recognition functions. A smartphone application was created to utilize 120 digit-triplets in noise as test material. An adaptive test procedure determined the speech reception threshold (SRT). Experiments were performed to determine headphones effects on the SRT and to establish normative data. Participants consisted of 40 normal-hearing subjects with thresholds ≤15 dB across the frequency spectrum (250-8000 Hz) and 186 subjects with normal-hearing in both ears, or normal-hearing in the better ear. The results show steep speech recognition functions with a slope of 20%/dB for digit-triplets presented in noise using the smartphone application. The results of five headphone types indicate that the smartphone-based hearing test is reliable and can be conducted using standard Android smartphone headphones or clinical headphones. A digits-in-noise hearing test was developed and validated for South Africa. The mean SRT and speech recognition functions correspond to previous developed telephone-based digits-in-noise tests.

Spontaneous Speech Collection for the CSR Corpus

DTIC Science & Technology

1992-01-01

Menlo Park, California 94025 1. ABSTRACT As part of a pilot data collection for DARPA’s Continuous Speech Recognition ( CSR ) speech corpus, SRI...International experi- mented with the collection of spontaneous speeoh material. The bulk of the CSR pilot data was read versions of news articles from...variable. 2. INTRODUCTION The CSR (Continuous Speech Recognition) Corpus collec- tion can be considered the successor to the Resource Man- agemen t

Eyes and ears: Using eye tracking and pupillometry to understand challenges to speech recognition.

PubMed

Van Engen, Kristin J; McLaughlin, Drew J

2018-05-04

Although human speech recognition is often experienced as relatively effortless, a number of common challenges can render the task more difficult. Such challenges may originate in talkers (e.g., unfamiliar accents, varying speech styles), the environment (e.g. noise), or in listeners themselves (e.g., hearing loss, aging, different native language backgrounds). Each of these challenges can reduce the intelligibility of spoken language, but even when intelligibility remains high, they can place greater processing demands on listeners. Noisy conditions, for example, can lead to poorer recall for speech, even when it has been correctly understood. Speech intelligibility measures, memory tasks, and subjective reports of listener difficulty all provide critical information about the effects of such challenges on speech recognition. Eye tracking and pupillometry complement these methods by providing objective physiological measures of online cognitive processing during listening. Eye tracking records the moment-to-moment direction of listeners' visual attention, which is closely time-locked to unfolding speech signals, and pupillometry measures the moment-to-moment size of listeners' pupils, which dilate in response to increased cognitive load. In this paper, we review the uses of these two methods for studying challenges to speech recognition. Copyright © 2018. Published by Elsevier B.V.

Diminutives facilitate word segmentation in natural speech: cross-linguistic evidence.

PubMed

Kempe, Vera; Brooks, Patricia J; Gillis, Steven; Samson, Graham

2007-06-01

Final-syllable invariance is characteristic of diminutives (e.g., doggie), which are a pervasive feature of the child-directed speech registers of many languages. Invariance in word endings has been shown to facilitate word segmentation (Kempe, Brooks, & Gillis, 2005) in an incidental-learning paradigm in which synthesized Dutch pseudonouns were used. To broaden the cross-linguistic evidence for this invariance effect and to increase its ecological validity, adult English speakers (n=276) were exposed to naturally spoken Dutch or Russian pseudonouns presented in sentence contexts. A forced choice test was given to assess target recognition, with foils comprising unfamiliar syllable combinations in Experiments 1 and 2 and syllable combinations straddling word boundaries in Experiment 3. A control group (n=210) received the recognition test with no prior exposure to targets. Recognition performance improved with increasing final-syllable rhyme invariance, with larger increases for the experimental group. This confirms that word ending invariance is a valid segmentation cue in artificial, as well as naturalistic, speech and that diminutives may aid segmentation in a number of languages.

Robust relationship between reading span and speech recognition in noise

PubMed Central

Souza, Pamela; Arehart, Kathryn

2015-01-01

Objective Working memory refers to a cognitive system that manages information processing and temporary storage. Recent work has demonstrated that individual differences in working memory capacity measured using a reading span task are related to ability to recognize speech in noise. In this project, we investigated whether the specific implementation of the reading span task influenced the strength of the relationship between working memory capacity and speech recognition. Design The relationship between speech recognition and working memory capacity was examined for two different working memory tests that varied in approach, using a within-subject design. Data consisted of audiometric results along with the two different working memory tests; one speech-in-noise test; and a reading comprehension test. Study sample The test group included 94 older adults with varying hearing loss and 30 younger adults with normal hearing. Results Listeners with poorer working memory capacity had more difficulty understanding speech in noise after accounting for age and degree of hearing loss. That relationship did not differ significantly between the two different implementations of reading span. Conclusions Our findings suggest that different implementations of a verbal reading span task do not affect the strength of the relationship between working memory capacity and speech recognition. PMID:25975360

Robust relationship between reading span and speech recognition in noise.

PubMed

Souza, Pamela; Arehart, Kathryn

2015-01-01

Working memory refers to a cognitive system that manages information processing and temporary storage. Recent work has demonstrated that individual differences in working memory capacity measured using a reading span task are related to ability to recognize speech in noise. In this project, we investigated whether the specific implementation of the reading span task influenced the strength of the relationship between working memory capacity and speech recognition. The relationship between speech recognition and working memory capacity was examined for two different working memory tests that varied in approach, using a within-subject design. Data consisted of audiometric results along with the two different working memory tests; one speech-in-noise test; and a reading comprehension test. The test group included 94 older adults with varying hearing loss and 30 younger adults with normal hearing. Listeners with poorer working memory capacity had more difficulty understanding speech in noise after accounting for age and degree of hearing loss. That relationship did not differ significantly between the two different implementations of reading span. Our findings suggest that different implementations of a verbal reading span task do not affect the strength of the relationship between working memory capacity and speech recognition.

Using Temporal Modulation Sensitivity to Select Stimulation Sites for Processor MAPs in Cochlear Implant Listeners

PubMed Central

Garadat, Soha N.; Zwolan, Teresa A.; Pfingst, Bryan E.

2013-01-01

Previous studies in our laboratory showed that temporal acuity as assessed by modulation detection thresholds (MDTs) varied across activation sites and that this site-to-site variability was subject specific. Using two 10-channel MAPs, the previous experiments showed that processor MAPs that had better across-site mean (ASM) MDTs yielded better speech recognition than MAPs with poorer ASM MDTs tested in the same subject. The current study extends our earlier work on developing more optimal fitting strategies to test the feasibility of using a site-selection approach in the clinical domain. This study examined the hypothesis that revising the clinical speech processor MAP for cochlear implant (CI) recipients by turning off selected sites that have poorer temporal acuity and reallocating frequencies to the remaining electrodes would lead to improved speech recognition. Twelve CI recipients participated in the experiments. We found that site selection procedure based on MDTs in the presence of a masker resulted in improved performance on consonant recognition and recognition of sentences in noise. In contrast, vowel recognition was poorer with the experimental MAP than with the clinical MAP, possibly due to reduced spectral resolution when sites were removed from the experimental MAP. Overall, these results suggest a promising path for improving recipient outcomes using personalized processor-fitting strategies based on a psychophysical measure of temporal acuity. PMID:23881208

[Perception of emotional intonation of noisy speech signal with different acoustic parameters by adults of different age and gender].

PubMed

Dmitrieva, E S; Gel'man, V Ia

2011-01-01

The listener-distinctive features of recognition of different emotional intonations (positive, negative and neutral) of male and female speakers in the presence or absence of background noise were studied in 49 adults aged 20-79 years. In all the listeners noise produced the most pronounced decrease in recognition accuracy for positive emotional intonation ("joy") as compared to other intonations, whereas it did not influence the recognition accuracy of "anger" in 65-79-year-old listeners. The higher emotion recognition rates of a noisy signal were observed for speech emotional intonations expressed by female speakers. Acoustic characteristics of noisy and clear speech signals underlying perception of speech emotional prosody were found for adult listeners of different age and gender.

Developing and Evaluating an Oral Skills Training Website Supported by Automatic Speech Recognition Technology

ERIC Educational Resources Information Center

Chen, Howard Hao-Jan

2011-01-01

Oral communication ability has become increasingly important to many EFL students. Several commercial software programs based on automatic speech recognition (ASR) technologies are available but their prices are not affordable for many students. This paper will demonstrate how the Microsoft Speech Application Software Development Kit (SASDK), a…

Vocal Tract Representation in the Recognition of Cerebral Palsied Speech

ERIC Educational Resources Information Center

Rudzicz, Frank; Hirst, Graeme; van Lieshout, Pascal

2012-01-01

Purpose: In this study, the authors explored articulatory information as a means of improving the recognition of dysarthric speech by machine. Method: Data were derived chiefly from the TORGO database of dysarthric articulation (Rudzicz, Namasivayam, & Wolff, 2011) in which motions of various points in the vocal tract are measured during speech.…

Micro-Based Speech Recognition: Instructional Innovation for Handicapped Learners.

ERIC Educational Resources Information Center

Horn, Carin E.; Scott, Brian L.

A new voice based learning system (VBLS), which allows the handicapped user to interact with a microcomputer by voice commands, is described. Speech or voice recognition is the computerized process of identifying a spoken word or phrase, including those resulting from speech impediments. This new technology is helpful to the severely physically…

Speech Recognition Software for Language Learning: Toward an Evaluation of Validity and Student Perceptions

ERIC Educational Resources Information Center

Cordier, Deborah

2009-01-01

A renewed focus on foreign language (FL) learning and speech for communication has resulted in computer-assisted language learning (CALL) software developed with Automatic Speech Recognition (ASR). ASR features for FL pronunciation (Lafford, 2004) are functional components of CALL designs used for FL teaching and learning. The ASR features…

Selecting cockpit functions for speech I/O technology

NASA Technical Reports Server (NTRS)

Simpson, C. A.

1985-01-01

A general methodology for the initial selection of functions for speech generation and speech recognition technology is discussed. The SCR (Stimulus/Central-Processing/Response) compatibility model of Wickens et al. (1983) is examined, and its application is demonstrated for a particular cockpit display problem. Some limits of the applicability of that model are illustrated in the context of predicting overall pilot-aircraft system performance. A program of system performance measurement is recommended for the evaluation of candidate systems. It is suggested that no one measure of system performance can necessarily be depended upon to the exclusion of others. Systems response time, system accuracy, and pilot ratings are all important measures. Finally, these measures must be collected in the context of the total flight task environment.

Noise Robust Speech Recognition Applied to Voice-Driven Wheelchair

NASA Astrophysics Data System (ADS)

Sasou, Akira; Kojima, Hiroaki

2009-12-01

Conventional voice-driven wheelchairs usually employ headset microphones that are capable of achieving sufficient recognition accuracy, even in the presence of surrounding noise. However, such interfaces require users to wear sensors such as a headset microphone, which can be an impediment, especially for the hand disabled. Conversely, it is also well known that the speech recognition accuracy drastically degrades when the microphone is placed far from the user. In this paper, we develop a noise robust speech recognition system for a voice-driven wheelchair. This system can achieve almost the same recognition accuracy as the headset microphone without wearing sensors. We verified the effectiveness of our system in experiments in different environments, and confirmed that our system can achieve almost the same recognition accuracy as the headset microphone without wearing sensors.

Lip-read me now, hear me better later: cross-modal transfer of talker-familiarity effects.

PubMed

Rosenblum, Lawrence D; Miller, Rachel M; Sanchez, Kauyumari

2007-05-01

There is evidence that for both auditory and visual speech perception, familiarity with the talker facilitates speech recognition. Explanations of these effects have concentrated on the retention of talker information specific to each of these modalities. It could be, however, that some amodal, talker-specific articulatory-style information facilitates speech perception in both modalities. If this is true, then experience with a talker in one modality should facilitate perception of speech from that talker in the other modality. In a test of this prediction, subjects were given about 1 hr of experience lipreading a talker and were then asked to recover speech in noise from either this same talker or a different talker. Results revealed that subjects who lip-read and heard speech from the same talker performed better on the speech-in-noise task than did subjects who lip-read from one talker and then heard speech from a different talker.

Speech Recognition in Noise by Children with and without Dyslexia: How is it Related to Reading?

PubMed

Nittrouer, Susan; Krieg, Letitia M; Lowenstein, Joanna H

2018-06-01

Developmental dyslexia is commonly viewed as a phonological deficit that makes it difficult to decode written language. But children with dyslexia typically exhibit other problems, as well, including poor speech recognition in noise. The purpose of this study was to examine whether the speech-in-noise problems of children with dyslexia are related to their reading problems, and if so, if a common underlying factor might explain both. The specific hypothesis examined was that a spectral processing disorder results in these children receiving smeared signals, which could explain both the diminished sensitivity to phonological structure - leading to reading problems - and the speech recognition in noise difficulties. The alternative hypothesis tested in this study was that children with dyslexia simply have broadly based language deficits. Ninety-seven children between the ages of 7 years; 10 months and 12 years; 9 months participated: 46 with dyslexia and 51 without dyslexia. Children were tested on two dependent measures: word reading and recognition in noise with two types of sentence materials: as unprocessed (UP) signals, and as spectrally smeared (SM) signals. Data were collected for four predictor variables: phonological awareness, vocabulary, grammatical knowledge, and digit span. Children with dyslexia showed deficits on both dependent and all predictor variables. Their scores for speech recognition in noise were poorer than those of children without dyslexia for both the UP and SM signals, but by equivalent amounts across signal conditions indicating that they were not disproportionately hindered by spectral distortion. Correlation analyses on scores from children with dyslexia showed that reading ability and speech-in-noise recognition were only mildly correlated, and each skill was related to different underlying abilities. No substantial evidence was found to support the suggestion that the reading and speech recognition in noise problems of children with dyslexia arise from a single factor that could be defined as a spectral processing disorder. The reading and speech recognition in noise deficits of these children appeared to be largely independent. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Characteristics, advantages, and limits of matrix tests].

PubMed

Brand, T; Wagener, K C

2017-03-01

Deterioration of communication abilities due to hearing problems is particularly relevant in listening situations with noise. Therefore, speech intelligibility tests in noise are required for audiological diagnostics and evaluation of hearing rehabilitation. This study analyzed the characteristics of matrix tests assessing the 50 % speech recognition threshold in noise. What are their advantages and limitations? Matrix tests are based on a matrix of 50 words (10 five-word sentences with same grammatical structure). In the standard setting, 20 sentences are presented using an adaptive procedure estimating the individual 50 % speech recognition threshold in noise. At present, matrix tests in 17 different languages are available. A high international comparability of matrix tests exists. The German language matrix test (OLSA, male speaker) has a reference 50 % speech recognition threshold of -7.1 (± 1.1) dB SNR. Before using a matrix test for the first time, the test person has to become familiar with the basic speech material using two training lists. Hereafter, matrix tests produce constant results even if repeated many times. Matrix tests are suitable for users of hearing aids and cochlear implants, particularly for assessment of benefit during the fitting process. Matrix tests can be performed in closed form and consequently with non-native listeners, even if the experimenter does not speak the test person's native language. Short versions of matrix tests are available for listeners with a shorter memory span, e.g., children.

Noisy text categorization.

PubMed

Vinciarelli, Alessandro

2005-12-01

This work presents categorization experiments performed over noisy texts. By noisy, we mean any text obtained through an extraction process (affected by errors) from media other than digital texts (e.g., transcriptions of speech recordings extracted with a recognition system). The performance of a categorization system over the clean and noisy (Word Error Rate between approximately 10 and approximately 50 percent) versions of the same documents is compared. The noisy texts are obtained through handwriting recognition and simulation of optical character recognition. The results show that the performance loss is acceptable for Recall values up to 60-70 percent depending on the noise sources. New measures of the extraction process performance, allowing a better explanation of the categorization results, are proposed.

Comparison of speech recognition with adaptive digital and FM remote microphone hearing assistance technology by listeners who use hearing aids.

PubMed

Thibodeau, Linda

2014-06-01

The purpose of this study was to compare the benefits of 3 types of remote microphone hearing assistance technology (HAT), adaptive digital broadband, adaptive frequency modulation (FM), and fixed FM, through objective and subjective measures of speech recognition in clinical and real-world settings. Participants included 11 adults, ages 16 to 78 years, with primarily moderate-to-severe bilateral hearing impairment (HI), who wore binaural behind-the-ear hearing aids; and 15 adults, ages 18 to 30 years, with normal hearing. Sentence recognition in quiet and in noise and subjective ratings were obtained in 3 conditions of wireless signal processing. Performance by the listeners with HI when using the adaptive digital technology was significantly better than that obtained with the FM technology, with the greatest benefits at the highest noise levels. The majority of listeners also preferred the digital technology when listening in a real-world noisy environment. The wireless technology allowed persons with HI to surpass persons with normal hearing in speech recognition in noise, with the greatest benefit occurring with adaptive digital technology. The use of adaptive digital technology combined with speechreading cues would allow persons with HI to engage in communication in environments that would have otherwise not been possible with traditional wireless technology.

Application of advanced speech technology in manned penetration bombers

NASA Astrophysics Data System (ADS)

North, R.; Lea, W.

1982-03-01

This report documents research on the potential use of speech technology in a manned penetration bomber aircraft (B-52/G and H). The objectives of the project were to analyze the pilot/copilot crewstation tasks over a three-hour-and forty-minute mission and determine the tasks that would benefit the most from conversion to speech recognition/generation, determine the technological feasibility of each of the identified tasks, and prioritize these tasks based on these criteria. Secondary objectives of the program were to enunciate research strategies in the application of speech technologies in airborne environments, and develop guidelines for briefing user commands on the potential of using speech technologies in the cockpit. The results of this study indicated that for the B-52 crewmember, speech recognition would be most beneficial for retrieving chart and procedural data that is contained in the flight manuals. Technological feasibility of these tasks indicated that the checklist and procedural retrieval tasks would be highly feasible for a speech recognition system.

Objective Assessment of Listening Effort: Coregistration of Pupillometry and EEG.

PubMed

Miles, Kelly; McMahon, Catherine; Boisvert, Isabelle; Ibrahim, Ronny; de Lissa, Peter; Graham, Petra; Lyxell, Björn

2017-01-01

Listening to speech in noise is effortful, particularly for people with hearing impairment. While it is known that effort is related to a complex interplay between bottom-up and top-down processes, the cognitive and neurophysiological mechanisms contributing to effortful listening remain unknown. Therefore, a reliable physiological measure to assess effort remains elusive. This study aimed to determine whether pupil dilation and alpha power change, two physiological measures suggested to index listening effort, assess similar processes. Listening effort was manipulated by parametrically varying spectral resolution (16- and 6-channel noise vocoding) and speech reception thresholds (SRT; 50% and 80%) while 19 young, normal-hearing adults performed a speech recognition task in noise. Results of off-line sentence scoring showed discrepancies between the target SRTs and the true performance obtained during the speech recognition task. For example, in the SRT80% condition, participants scored an average of 64.7%. Participants' true performance levels were therefore used for subsequent statistical modelling. Results showed that both measures appeared to be sensitive to changes in spectral resolution (channel vocoding), while pupil dilation only was also significantly related to their true performance levels (%) and task accuracy (i.e., whether the response was correctly or partially recalled). The two measures were not correlated, suggesting they each may reflect different cognitive processes involved in listening effort. This combination of findings contributes to a growing body of research aiming to develop an objective measure of listening effort.

Development of equally intelligible Telugu sentence-lists to test speech recognition in noise.

PubMed

Tanniru, Kishore; Narne, Vijaya Kumar; Jain, Chandni; Konadath, Sreeraj; Singh, Niraj Kumar; Sreenivas, K J Ramadevi; K, Anusha

2017-09-01

To develop sentence lists in the Telugu language for the assessment of speech recognition threshold (SRT) in the presence of background noise through identification of the mean signal-to-noise ratio required to attain a 50% sentence recognition score (SRTn). This study was conducted in three phases. The first phase involved the selection and recording of Telugu sentences. In the second phase, 20 lists, each consisting of 10 sentences with equal intelligibility, were formulated using a numerical optimisation procedure. In the third phase, the SRTn of the developed lists was estimated using adaptive procedures on individuals with normal hearing. A total of 68 native Telugu speakers with normal hearing participated in the study. Of these, 18 (including the speakers) performed on various subjective measures in first phase, 20 performed on sentence/word recognition in noise for second phase and 30 participated in the list equivalency procedures in third phase. In all, 15 lists of comparable difficulty were formulated as test material. The mean SRTn across these lists corresponded to -2.74 (SD = 0.21). The developed sentence lists provided a valid and reliable tool to measure SRTn in Telugu native speakers.

The Effect of Dynamic Pitch on Speech Recognition in Temporally Modulated Noise

ERIC Educational Resources Information Center

Shen, Jung; Souza, Pamela E.

2017-01-01

Purpose: This study investigated the effect of dynamic pitch in target speech on older and younger listeners' speech recognition in temporally modulated noise. First, we examined whether the benefit from dynamic-pitch cues depends on the temporal modulation of noise. Second, we tested whether older listeners can benefit from dynamic-pitch cues for…

Introduction and Overview of the Vicens-Reddy Speech Recognition System.

ERIC Educational Resources Information Center

Kameny, Iris; Ritea, H.

The Vicens-Reddy System is unique in the sense that it approaches the problem of speech recognition as a whole, rather than treating particular aspects of the problems as in previous attempts. For example, where earlier systems treated only segmentation of speech into phoneme groups, or detected phonemes in a given context, the Vicens-Reddy System…

Accommodation and Compliance Series: Employees with Arthritis

MedlinePlus

... handed keyboard, an articulating keyboard tray, speech recognition software, a trackball, and office equipment for a workstation ... space heater, additional window insulation, and speech recognition software. An insurance clerk with arthritis from systemic lupus ...

[Research on Barrier-free Home Environment System Based on Speech Recognition].

PubMed

Zhu, Husheng; Yu, Hongliu; Shi, Ping; Fang, Youfang; Jian, Zhuo

2015-10-01

The number of people with physical disabilities is increasing year by year, and the trend of population aging is more and more serious. In order to improve the quality of the life, a control system of accessible home environment for the patients with serious disabilities was developed to control the home electrical devices with the voice of the patients. The control system includes a central control platform, a speech recognition module, a terminal operation module, etc. The system combines the speech recognition control technology and wireless information transmission technology with the embedded mobile computing technology, and interconnects the lamp, electronic locks, alarms, TV and other electrical devices in the home environment as a whole system through a wireless network node. The experimental results showed that speech recognition success rate was more than 84% in the home environment.

Assessing spoken word recognition in children who are deaf or hard of hearing: a translational approach.

PubMed

Kirk, Karen Iler; Prusick, Lindsay; French, Brian; Gotch, Chad; Eisenberg, Laurie S; Young, Nancy

2012-06-01

Under natural conditions, listeners use both auditory and visual speech cues to extract meaning from speech signals containing many sources of variability. However, traditional clinical tests of spoken word recognition routinely employ isolated words or sentences produced by a single talker in an auditory-only presentation format. The more central cognitive processes used during multimodal integration, perceptual normalization, and lexical discrimination that may contribute to individual variation in spoken word recognition performance are not assessed in conventional tests of this kind. In this article, we review our past and current research activities aimed at developing a series of new assessment tools designed to evaluate spoken word recognition in children who are deaf or hard of hearing. These measures are theoretically motivated by a current model of spoken word recognition and also incorporate "real-world" stimulus variability in the form of multiple talkers and presentation formats. The goal of this research is to enhance our ability to estimate real-world listening skills and to predict benefit from sensory aid use in children with varying degrees of hearing loss. American Academy of Audiology.

Speech-recognition interfaces for music information retrieval

NASA Astrophysics Data System (ADS)

Goto, Masataka

2005-09-01

This paper describes two hands-free music information retrieval (MIR) systems that enable a user to retrieve and play back a musical piece by saying its title or the artist's name. Although various interfaces for MIR have been proposed, speech-recognition interfaces suitable for retrieving musical pieces have not been studied. Our MIR-based jukebox systems employ two different speech-recognition interfaces for MIR, speech completion and speech spotter, which exploit intentionally controlled nonverbal speech information in original ways. The first is a music retrieval system with the speech-completion interface that is suitable for music stores and car-driving situations. When a user only remembers part of the name of a musical piece or an artist and utters only a remembered fragment, the system helps the user recall and enter the name by completing the fragment. The second is a background-music playback system with the speech-spotter interface that can enrich human-human conversation. When a user is talking to another person, the system allows the user to enter voice commands for music playback control by spotting a special voice-command utterance in face-to-face or telephone conversations. Experimental results from use of these systems have demonstrated the effectiveness of the speech-completion and speech-spotter interfaces. (Video clips: http://staff.aist.go.jp/m.goto/MIR/speech-if.html)

Auditory-Motor Processing of Speech Sounds

PubMed Central

Möttönen, Riikka; Dutton, Rebekah; Watkins, Kate E.

2013-01-01

The motor regions that control movements of the articulators activate during listening to speech and contribute to performance in demanding speech recognition and discrimination tasks. Whether the articulatory motor cortex modulates auditory processing of speech sounds is unknown. Here, we aimed to determine whether the articulatory motor cortex affects the auditory mechanisms underlying discrimination of speech sounds in the absence of demanding speech tasks. Using electroencephalography, we recorded responses to changes in sound sequences, while participants watched a silent video. We also disrupted the lip or the hand representation in left motor cortex using transcranial magnetic stimulation. Disruption of the lip representation suppressed responses to changes in speech sounds, but not piano tones. In contrast, disruption of the hand representation had no effect on responses to changes in speech sounds. These findings show that disruptions within, but not outside, the articulatory motor cortex impair automatic auditory discrimination of speech sounds. The findings provide evidence for the importance of auditory-motor processes in efficient neural analysis of speech sounds. PMID:22581846

Auditory performance and subjective benefits in adults with congenital or prelinguistic deafness who receive cochlear implants during adulthood.

PubMed

Duchesne, Louise; Millette, Isabelle; Bhérer, Maurice; Gobeil, Suzie

2017-05-01

(1) To describe auditory performance and subjective benefits in adults with congenital or prelingual deafness who received a cochlear implant (CI) during adolescence or adulthood, and (2) to examine the benefits as experienced by these CI users. Twenty-one adults aged 23-65 years participated in the study. All had a congenital or prelingual deafness (onset before age 3). They received a CI between the age of 16 and 61 years (mean age: 31). Speech recognition scores before and after implantation were computed and a questionnaire on subjective benefits (French adaptation of the Adult Cochlear Implant Questionnaire, designed by Zwolan and collaborators (1996, Self-report of CI use and satisfaction by prelingually deafened adults. Ear and Hearing, 17(3): 198-210) was administered. Semi-structured interviews were subsequently conducted with a subsample of seven participants. Speech recognition scores after implantation ranged from 0 to 95%. Despite large inter-individual variability, most participants expressed high levels satisfaction and overall usefulness. Correlational analyses showed that speech recognition performance was moderately associated with subjective benefits. Data from the interviews revealed that the underlying sources of satisfaction with the implant are related to the discovery and enjoyment of environmental sounds, easier lip-reading, and improvement of self-confidence during communicative interactions. CI benefits are mostly subjective in this particular population: descriptive and qualitative approaches allow us to obtain a nuanced portrait of their experience and provide us with important elements that are not easily measurable with tests and scores.

A comparative intelligibility study of single-microphone noise reduction algorithms.

PubMed

Hu, Yi; Loizou, Philipos C

2007-09-01

The evaluation of intelligibility of noise reduction algorithms is reported. IEEE sentences and consonants were corrupted by four types of noise including babble, car, street and train at two signal-to-noise ratio levels (0 and 5 dB), and then processed by eight speech enhancement methods encompassing four classes of algorithms: spectral subtractive, sub-space, statistical model based and Wiener-type algorithms. The enhanced speech was presented to normal-hearing listeners for identification. With the exception of a single noise condition, no algorithm produced significant improvements in speech intelligibility. Information transmission analysis of the consonant confusion matrices indicated that no algorithm improved significantly the place feature score, significantly, which is critically important for speech recognition. The algorithms which were found in previous studies to perform the best in terms of overall quality, were not the same algorithms that performed the best in terms of speech intelligibility. The subspace algorithm, for instance, was previously found to perform the worst in terms of overall quality, but performed well in the present study in terms of preserving speech intelligibility. Overall, the analysis of consonant confusion matrices suggests that in order for noise reduction algorithms to improve speech intelligibility, they need to improve the place and manner feature scores.

Research on Spoken Dialogue Systems

NASA Technical Reports Server (NTRS)

Aist, Gregory; Hieronymus, James; Dowding, John; Hockey, Beth Ann; Rayner, Manny; Chatzichrisafis, Nikos; Farrell, Kim; Renders, Jean-Michel

2010-01-01

Research in the field of spoken dialogue systems has been performed with the goal of making such systems more robust and easier to use in demanding situations. The term "spoken dialogue systems" signifies unified software systems containing speech-recognition, speech-synthesis, dialogue management, and ancillary components that enable human users to communicate, using natural spoken language or nearly natural prescribed spoken language, with other software systems that provide information and/or services.

Objective voice and speech analysis of persons with chronic hoarseness by prosodic analysis of speech samples.

PubMed

Haderlein, Tino; Döllinger, Michael; Matoušek, Václav; Nöth, Elmar

2016-10-01

Automatic voice assessment is often performed using sustained vowels. In contrast, speech analysis of read-out texts can be applied to voice and speech assessment. Automatic speech recognition and prosodic analysis were used to find regression formulae between automatic and perceptual assessment of four voice and four speech criteria. The regression was trained with 21 men and 62 women (average age 49.2 years) and tested with another set of 24 men and 49 women (48.3 years), all suffering from chronic hoarseness. They read the text 'Der Nordwind und die Sonne' ('The North Wind and the Sun'). Five voice and speech therapists evaluated the data on 5-point Likert scales. Ten prosodic and recognition accuracy measures (features) were identified which describe all the examined criteria. Inter-rater correlation within the expert group was between r = 0.63 for the criterion 'match of breath and sense units' and r = 0.87 for the overall voice quality. Human-machine correlation was between r = 0.40 for the match of breath and sense units and r = 0.82 for intelligibility. The perceptual ratings of different criteria were highly correlated with each other. Likewise, the feature sets modeling the criteria were very similar. The automatic method is suitable for assessing chronic hoarseness in general and for subgroups of functional and organic dysphonia. In its current version, it is almost as reliable as a randomly picked rater from a group of voice and speech therapists.

Some factors underlying individual differences in speech recognition on PRESTO: a first report.

PubMed

Tamati, Terrin N; Gilbert, Jaimie L; Pisoni, David B

2013-01-01

Previous studies investigating speech recognition in adverse listening conditions have found extensive variability among individual listeners. However, little is currently known about the core underlying factors that influence speech recognition abilities. To investigate sensory, perceptual, and neurocognitive differences between good and poor listeners on the Perceptually Robust English Sentence Test Open-set (PRESTO), a new high-variability sentence recognition test under adverse listening conditions. Participants who fell in the upper quartile (HiPRESTO listeners) or lower quartile (LoPRESTO listeners) on key word recognition on sentences from PRESTO in multitalker babble completed a battery of behavioral tasks and self-report questionnaires designed to investigate real-world hearing difficulties, indexical processing skills, and neurocognitive abilities. Young, normal-hearing adults (N = 40) from the Indiana University community participated in the current study. Participants' assessment of their own real-world hearing difficulties was measured with a self-report questionnaire on situational hearing and hearing health history. Indexical processing skills were assessed using a talker discrimination task, a gender discrimination task, and a forced-choice regional dialect categorization task. Neurocognitive abilities were measured with the Auditory Digit Span Forward (verbal short-term memory) and Digit Span Backward (verbal working memory) tests, the Stroop Color and Word Test (attention/inhibition), the WordFam word familiarity test (vocabulary size), the Behavioral Rating Inventory of Executive Function-Adult Version (BRIEF-A) self-report questionnaire on executive function, and two performance subtests of the Wechsler Abbreviated Scale of Intelligence (WASI) Performance Intelligence Quotient (IQ; nonverbal intelligence). Scores on self-report questionnaires and behavioral tasks were tallied and analyzed by listener group (HiPRESTO and LoPRESTO). The extreme groups did not differ overall on self-reported hearing difficulties in real-world listening environments. However, an item-by-item analysis of questions revealed that LoPRESTO listeners reported significantly greater difficulty understanding speakers in a public place. HiPRESTO listeners were significantly more accurate than LoPRESTO listeners at gender discrimination and regional dialect categorization, but they did not differ on talker discrimination accuracy or response time, or gender discrimination response time. HiPRESTO listeners also had longer forward and backward digit spans, higher word familiarity ratings on the WordFam test, and lower (better) scores for three individual items on the BRIEF-A questionnaire related to cognitive load. The two groups did not differ on the Stroop Color and Word Test or either of the WASI performance IQ subtests. HiPRESTO listeners and LoPRESTO listeners differed in indexical processing abilities, short-term and working memory capacity, vocabulary size, and some domains of executive functioning. These findings suggest that individual differences in the ability to encode and maintain highly detailed episodic information in speech may underlie the variability observed in speech recognition performance in adverse listening conditions using high-variability PRESTO sentences in multitalker babble. American Academy of Audiology.

Some Factors Underlying Individual Differences in Speech Recognition on PRESTO: A First Report

PubMed Central

Tamati, Terrin N.; Gilbert, Jaimie L.; Pisoni, David B.

2013-01-01

Background Previous studies investigating speech recognition in adverse listening conditions have found extensive variability among individual listeners. However, little is currently known about the core, underlying factors that influence speech recognition abilities. Purpose To investigate sensory, perceptual, and neurocognitive differences between good and poor listeners on PRESTO, a new high-variability sentence recognition test under adverse listening conditions. Research Design Participants who fell in the upper quartile (HiPRESTO listeners) or lower quartile (LoPRESTO listeners) on key word recognition on sentences from PRESTO in multitalker babble completed a battery of behavioral tasks and self-report questionnaires designed to investigate real-world hearing difficulties, indexical processing skills, and neurocognitive abilities. Study Sample Young, normal-hearing adults (N = 40) from the Indiana University community participated in the current study. Data Collection and Analysis Participants’ assessment of their own real-world hearing difficulties was measured with a self-report questionnaire on situational hearing and hearing health history. Indexical processing skills were assessed using a talker discrimination task, a gender discrimination task, and a forced-choice regional dialect categorization task. Neurocognitive abilities were measured with the Auditory Digit Span Forward (verbal short-term memory) and Digit Span Backward (verbal working memory) tests, the Stroop Color and Word Test (attention/inhibition), the WordFam word familiarity test (vocabulary size), the BRIEF-A self-report questionnaire on executive function, and two performance subtests of the WASI Performance IQ (non-verbal intelligence). Scores on self-report questionnaires and behavioral tasks were tallied and analyzed by listener group (HiPRESTO and LoPRESTO). Results The extreme groups did not differ overall on self-reported hearing difficulties in real-world listening environments. However, an item-by-item analysis of questions revealed that LoPRESTO listeners reported significantly greater difficulty understanding speakers in a public place. HiPRESTO listeners were significantly more accurate than LoPRESTO listeners at gender discrimination and regional dialect categorization, but they did not differ on talker discrimination accuracy or response time, or gender discrimination response time. HiPRESTO listeners also had longer forward and backward digit spans, higher word familiarity ratings on the WordFam test, and lower (better) scores for three individual items on the BRIEF-A questionnaire related to cognitive load. The two groups did not differ on the Stroop Color and Word Test or either of the WASI performance IQ subtests. Conclusions HiPRESTO listeners and LoPRESTO listeners differed in indexical processing abilities, short-term and working memory capacity, vocabulary size, and some domains of executive functioning. These findings suggest that individual differences in the ability to encode and maintain highly detailed episodic information in speech may underlie the variability observed in speech recognition performance in adverse listening conditions using high-variability PRESTO sentences in multitalker babble. PMID:24047949

Word segmentation in phonemically identical and prosodically different sequences using cochlear implants: A case study.

PubMed

Basirat, Anahita

2017-01-01

Cochlear implant (CI) users frequently achieve good speech understanding based on phoneme and word recognition. However, there is a significant variability between CI users in processing prosody. The aim of this study was to examine the abilities of an excellent CI user to segment continuous speech using intonational cues. A post-lingually deafened adult CI user and 22 normal hearing (NH) subjects segmented phonemically identical and prosodically different sequences in French such as 'l'affiche' (the poster) versus 'la fiche' (the sheet), both [lafiʃ]. All participants also completed a minimal pair discrimination task. Stimuli were presented in auditory-only and audiovisual presentation modalities. The performance of the CI user in the minimal pair discrimination task was 97% in the auditory-only and 100% in the audiovisual condition. In the segmentation task, contrary to the NH participants, the performance of the CI user did not differ from the chance level. Visual speech did not improve word segmentation. This result suggests that word segmentation based on intonational cues is challenging when using CIs even when phoneme/word recognition is very well rehabilitated. This finding points to the importance of the assessment of CI users' skills in prosody processing and the need for specific interventions focusing on this aspect of speech communication.

Dynamic relation between working memory capacity and speech recognition in noise during the first 6 months of hearing aid use.

PubMed

Ng, Elaine H N; Classon, Elisabet; Larsby, Birgitta; Arlinger, Stig; Lunner, Thomas; Rudner, Mary; Rönnberg, Jerker

2014-11-23

The present study aimed to investigate the changing relationship between aided speech recognition and cognitive function during the first 6 months of hearing aid use. Twenty-seven first-time hearing aid users with symmetrical mild to moderate sensorineural hearing loss were recruited. Aided speech recognition thresholds in noise were obtained in the hearing aid fitting session as well as at 3 and 6 months postfitting. Cognitive abilities were assessed using a reading span test, which is a measure of working memory capacity, and a cognitive test battery. Results showed a significant correlation between reading span and speech reception threshold during the hearing aid fitting session. This relation was significantly weakened over the first 6 months of hearing aid use. Multiple regression analysis showed that reading span was the main predictor of speech recognition thresholds in noise when hearing aids were first fitted, but that the pure-tone average hearing threshold was the main predictor 6 months later. One way of explaining the results is that working memory capacity plays a more important role in speech recognition in noise initially rather than after 6 months of use. We propose that new hearing aid users engage working memory capacity to recognize unfamiliar processed speech signals because the phonological form of these signals cannot be automatically matched to phonological representations in long-term memory. As familiarization proceeds, the mismatch effect is alleviated, and the engagement of working memory capacity is reduced. © The Author(s) 2014.

A Speech Recognition-based Solution for the Automatic Detection of Mild Cognitive Impairment from Spontaneous Speech

PubMed Central

Tóth, László; Hoffmann, Ildikó; Gosztolya, Gábor; Vincze, Veronika; Szatlóczki, Gréta; Bánréti, Zoltán; Pákáski, Magdolna; Kálmán, János

2018-01-01

Background: Even today the reliable diagnosis of the prodromal stages of Alzheimer’s disease (AD) remains a great challenge. Our research focuses on the earliest detectable indicators of cognitive de-cline in mild cognitive impairment (MCI). Since the presence of language impairment has been reported even in the mild stage of AD, the aim of this study is to develop a sensitive neuropsychological screening method which is based on the analysis of spontaneous speech production during performing a memory task. In the future, this can form the basis of an Internet-based interactive screening software for the recognition of MCI. Methods: Participants were 38 healthy controls and 48 clinically diagnosed MCI patients. The provoked spontaneous speech by asking the patients to recall the content of 2 short black and white films (one direct, one delayed), and by answering one question. Acoustic parameters (hesitation ratio, speech tempo, length and number of silent and filled pauses, length of utterance) were extracted from the recorded speech sig-nals, first manually (using the Praat software), and then automatically, with an automatic speech recogni-tion (ASR) based tool. First, the extracted parameters were statistically analyzed. Then we applied machine learning algorithms to see whether the MCI and the control group can be discriminated automatically based on the acoustic features. Results: The statistical analysis showed significant differences for most of the acoustic parameters (speech tempo, articulation rate, silent pause, hesitation ratio, length of utterance, pause-per-utterance ratio). The most significant differences between the two groups were found in the speech tempo in the delayed recall task, and in the number of pauses for the question-answering task. The fully automated version of the analysis process – that is, using the ASR-based features in combination with machine learning - was able to separate the two classes with an F1-score of 78.8%. Conclusion: The temporal analysis of spontaneous speech can be exploited in implementing a new, auto-matic detection-based tool for screening MCI for the community. PMID:29165085

A Speech Recognition-based Solution for the Automatic Detection of Mild Cognitive Impairment from Spontaneous Speech.

PubMed

Toth, Laszlo; Hoffmann, Ildiko; Gosztolya, Gabor; Vincze, Veronika; Szatloczki, Greta; Banreti, Zoltan; Pakaski, Magdolna; Kalman, Janos

2018-01-01

Even today the reliable diagnosis of the prodromal stages of Alzheimer's disease (AD) remains a great challenge. Our research focuses on the earliest detectable indicators of cognitive decline in mild cognitive impairment (MCI). Since the presence of language impairment has been reported even in the mild stage of AD, the aim of this study is to develop a sensitive neuropsychological screening method which is based on the analysis of spontaneous speech production during performing a memory task. In the future, this can form the basis of an Internet-based interactive screening software for the recognition of MCI. Participants were 38 healthy controls and 48 clinically diagnosed MCI patients. The provoked spontaneous speech by asking the patients to recall the content of 2 short black and white films (one direct, one delayed), and by answering one question. Acoustic parameters (hesitation ratio, speech tempo, length and number of silent and filled pauses, length of utterance) were extracted from the recorded speech signals, first manually (using the Praat software), and then automatically, with an automatic speech recognition (ASR) based tool. First, the extracted parameters were statistically analyzed. Then we applied machine learning algorithms to see whether the MCI and the control group can be discriminated automatically based on the acoustic features. The statistical analysis showed significant differences for most of the acoustic parameters (speech tempo, articulation rate, silent pause, hesitation ratio, length of utterance, pause-per-utterance ratio). The most significant differences between the two groups were found in the speech tempo in the delayed recall task, and in the number of pauses for the question-answering task. The fully automated version of the analysis process - that is, using the ASR-based features in combination with machine learning - was able to separate the two classes with an F1-score of 78.8%. The temporal analysis of spontaneous speech can be exploited in implementing a new, automatic detection-based tool for screening MCI for the community. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Institute for the Study of Human Capabilities Summary Descriptions of Research for the Period September 1988 through June 1989

DTIC Science & Technology

1989-06-01

12 1.7 Application of the Modified Speech Transmission Index to Monaural and Binaural Speech Recognition in Normal and Impaired...describe all of the data from both groups. 1.7 Application of the Modified Speech Transmission Index to Monaural and Binaural Speech Recognition in...were obtained for materials presented to each ear separately (monaurally) and to both ears ( binaurally ). Results from the normal listeners are accurately

Emotion Recognition from Chinese Speech for Smart Affective Services Using a Combination of SVM and DBN

PubMed Central

Zhu, Lianzhang; Chen, Leiming; Zhao, Dehai

2017-01-01

Accurate emotion recognition from speech is important for applications like smart health care, smart entertainment, and other smart services. High accuracy emotion recognition from Chinese speech is challenging due to the complexities of the Chinese language. In this paper, we explore how to improve the accuracy of speech emotion recognition, including speech signal feature extraction and emotion classification methods. Five types of features are extracted from a speech sample: mel frequency cepstrum coefficient (MFCC), pitch, formant, short-term zero-crossing rate and short-term energy. By comparing statistical features with deep features extracted by a Deep Belief Network (DBN), we attempt to find the best features to identify the emotion status for speech. We propose a novel classification method that combines DBN and SVM (support vector machine) instead of using only one of them. In addition, a conjugate gradient method is applied to train DBN in order to speed up the training process. Gender-dependent experiments are conducted using an emotional speech database created by the Chinese Academy of Sciences. The results show that DBN features can reflect emotion status better than artificial features, and our new classification approach achieves an accuracy of 95.8%, which is higher than using either DBN or SVM separately. Results also show that DBN can work very well for small training databases if it is properly designed. PMID:28737705

Auditory and Non-Auditory Contributions for Unaided Speech Recognition in Noise as a Function of Hearing Aid Use

PubMed Central

Gieseler, Anja; Tahden, Maike A. S.; Thiel, Christiane M.; Wagener, Kirsten C.; Meis, Markus; Colonius, Hans

2017-01-01

Differences in understanding speech in noise among hearing-impaired individuals cannot be explained entirely by hearing thresholds alone, suggesting the contribution of other factors beyond standard auditory ones as derived from the audiogram. This paper reports two analyses addressing individual differences in the explanation of unaided speech-in-noise performance among n = 438 elderly hearing-impaired listeners (mean = 71.1 ± 5.8 years). The main analysis was designed to identify clinically relevant auditory and non-auditory measures for speech-in-noise prediction using auditory (audiogram, categorical loudness scaling) and cognitive tests (verbal-intelligence test, screening test of dementia), as well as questionnaires assessing various self-reported measures (health status, socio-economic status, and subjective hearing problems). Using stepwise linear regression analysis, 62% of the variance in unaided speech-in-noise performance was explained, with measures Pure-tone average (PTA), Age, and Verbal intelligence emerging as the three most important predictors. In the complementary analysis, those individuals with the same hearing loss profile were separated into hearing aid users (HAU) and non-users (NU), and were then compared regarding potential differences in the test measures and in explaining unaided speech-in-noise recognition. The groupwise comparisons revealed significant differences in auditory measures and self-reported subjective hearing problems, while no differences in the cognitive domain were found. Furthermore, groupwise regression analyses revealed that Verbal intelligence had a predictive value in both groups, whereas Age and PTA only emerged significant in the group of hearing aid NU. PMID:28270784

Auditory and Non-Auditory Contributions for Unaided Speech Recognition in Noise as a Function of Hearing Aid Use.

PubMed

Gieseler, Anja; Tahden, Maike A S; Thiel, Christiane M; Wagener, Kirsten C; Meis, Markus; Colonius, Hans

2017-01-01

Differences in understanding speech in noise among hearing-impaired individuals cannot be explained entirely by hearing thresholds alone, suggesting the contribution of other factors beyond standard auditory ones as derived from the audiogram. This paper reports two analyses addressing individual differences in the explanation of unaided speech-in-noise performance among n = 438 elderly hearing-impaired listeners ( mean = 71.1 ± 5.8 years). The main analysis was designed to identify clinically relevant auditory and non-auditory measures for speech-in-noise prediction using auditory (audiogram, categorical loudness scaling) and cognitive tests (verbal-intelligence test, screening test of dementia), as well as questionnaires assessing various self-reported measures (health status, socio-economic status, and subjective hearing problems). Using stepwise linear regression analysis, 62% of the variance in unaided speech-in-noise performance was explained, with measures Pure-tone average (PTA), Age , and Verbal intelligence emerging as the three most important predictors. In the complementary analysis, those individuals with the same hearing loss profile were separated into hearing aid users (HAU) and non-users (NU), and were then compared regarding potential differences in the test measures and in explaining unaided speech-in-noise recognition. The groupwise comparisons revealed significant differences in auditory measures and self-reported subjective hearing problems, while no differences in the cognitive domain were found. Furthermore, groupwise regression analyses revealed that Verbal intelligence had a predictive value in both groups, whereas Age and PTA only emerged significant in the group of hearing aid NU.

Hearing Handicap and Speech Recognition Correlate With Self-Reported Listening Effort and Fatigue.

PubMed

Alhanbali, Sara; Dawes, Piers; Lloyd, Simon; Munro, Kevin J

To investigate the correlations between hearing handicap, speech recognition, listening effort, and fatigue. Eighty-four adults with hearing loss (65 to 85 years) completed three self-report questionnaires: the Fatigue Assessment Scale, the Effort Assessment Scale, and the Hearing Handicap Inventory for Elderly. Audiometric assessment included pure-tone audiometry and speech recognition in noise. There was a significant positive correlation between handicap and fatigue (r = 0.39, p < 0.05) and handicap and effort (r = 0.73, p < 0.05). There were significant (but lower) correlations between speech recognition and fatigue (r = 0.22, p < 0.05) or effort (r = 0.32, p< 0.05). There was no significant correlation between hearing level and fatigue or effort. Hearing handicap and speech recognition both correlate with self-reported listening effort and fatigue, which is consistent with a model of listening effort and fatigue where perceived difficulty is related to sustained effort and fatigue for unrewarding tasks over which the listener has low control. A clinical implication is that encouraging clients to recognize and focus on the pleasure and positive experiences of listening may result in greater satisfaction and benefit from hearing aid use.

Development of coffee maker service robot using speech and face recognition systems using POMDP

NASA Astrophysics Data System (ADS)

Budiharto, Widodo; Meiliana; Santoso Gunawan, Alexander Agung

2016-07-01

There are many development of intelligent service robot in order to interact with user naturally. This purpose can be done by embedding speech and face recognition ability on specific tasks to the robot. In this research, we would like to propose Intelligent Coffee Maker Robot which the speech recognition is based on Indonesian language and powered by statistical dialogue systems. This kind of robot can be used in the office, supermarket or restaurant. In our scenario, robot will recognize user's face and then accept commands from the user to do an action, specifically in making a coffee. Based on our previous work, the accuracy for speech recognition is about 86% and face recognition is about 93% in laboratory experiments. The main problem in here is to know the intention of user about how sweetness of the coffee. The intelligent coffee maker robot should conclude the user intention through conversation under unreliable automatic speech in noisy environment. In this paper, this spoken dialog problem is treated as a partially observable Markov decision process (POMDP). We describe how this formulation establish a promising framework by empirical results. The dialog simulations are presented which demonstrate significant quantitative outcome.

Financial and workflow analysis of radiology reporting processes in the planning phase of implementation of a speech recognition system

NASA Astrophysics Data System (ADS)

Whang, Tom; Ratib, Osman M.; Umamoto, Kathleen; Grant, Edward G.; McCoy, Michael J.

2002-05-01

The goal of this study is to determine the financial value and workflow improvements achievable by replacing traditional transcription services with a speech recognition system in a large, university hospital setting. Workflow metrics were measured at two hospitals, one of which exclusively uses a transcription service (UCLA Medical Center), and the other which exclusively uses speech recognition (West Los Angeles VA Hospital). Workflow metrics include time spent per report (the sum of time spent interpreting, dictating, reviewing, and editing), transcription turnaround, and total report turnaround. Compared to traditional transcription, speech recognition resulted in radiologists spending 13-32% more time per report, but it also resulted in reduction of report turnaround time by 22-62% and reduction of marginal cost per report by 94%. The model developed here helps justify the introduction of a speech recognition system by showing that the benefits of reduced operating costs and decreased turnaround time outweigh the cost of increased time spent per report. Whether the ultimate goal is to achieve a financial objective or to improve operational efficiency, it is important to conduct a thorough analysis of workflow before implementation.

Effects of cooperating and conflicting cues on speech intonation recognition by cochlear implant users and normal hearing listeners.

PubMed

Peng, Shu-Chen; Lu, Nelson; Chatterjee, Monita

2009-01-01

Cochlear implant (CI) recipients have only limited access to fundamental frequency (F0) information, and thus exhibit deficits in speech intonation recognition. For speech intonation, F0 serves as the primary cue, and other potential acoustic cues (e.g. intensity properties) may also contribute. This study examined the effects of cooperating or conflicting acoustic cues on speech intonation recognition by adult CI and normal hearing (NH) listeners with full-spectrum and spectrally degraded speech stimuli. Identification of speech intonation that signifies question and statement contrasts was measured in 13 CI recipients and 4 NH listeners, using resynthesized bi-syllabic words, where F0 and intensity properties were systematically manipulated. The stimulus set was comprised of tokens whose acoustic cues (i.e. F0 contour and intensity patterns) were either cooperating or conflicting. Subjects identified if each stimulus is a 'statement' or a 'question' in a single-interval, 2-alternative forced-choice (2AFC) paradigm. Logistic models were fitted to the data, and estimated coefficients were compared under cooperating and conflicting conditions, between the subject groups (CI vs. NH), and under full-spectrum and spectrally degraded conditions for NH listeners. The results indicated that CI listeners' intonation recognition was enhanced by cooperating F0 contour and intensity cues, but was adversely affected by these cues being conflicting. On the other hand, with full-spectrum stimuli, NH listeners' intonation recognition was not affected by cues being cooperating or conflicting. The effects of cues being cooperating or conflicting were comparable between the CI group and NH listeners with spectrally degraded stimuli. These findings suggest the importance of taking multiple acoustic sources for speech recognition into consideration in aural rehabilitation for CI recipients. Copyright (C) 2009 S. Karger AG, Basel.

Effects of cooperating and conflicting cues on speech intonation recognition by cochlear implant users and normal hearing listeners

PubMed Central

Peng, Shu-Chen; Lu, Nelson; Chatterjee, Monita

2009-01-01

Cochlear implant (CI) recipients have only limited access to fundamental frequency (F0) information, and thus exhibit deficits in speech intonation recognition. For speech intonation, F0 serves as the primary cue, and other potential acoustic cues (e.g., intensity properties) may also contribute. This study examined the effects of acoustic cues being cooperating or conflicting on speech intonation recognition by adult cochlear implant (CI), and normal-hearing (NH) listeners with full-spectrum and spectrally degraded speech stimuli. Identification of speech intonation that signifies question and statement contrasts was measured in 13 CI recipients and 4 NH listeners, using resynthesized bi-syllabic words, where F0 and intensity properties were systematically manipulated. The stimulus set was comprised of tokens whose acoustic cues, i.e., F0 contour and intensity patterns, were either cooperating or conflicting. Subjects identified if each stimulus is a “statement” or a “question” in a single-interval, two-alternative forced-choice (2AFC) paradigm. Logistic models were fitted to the data, and estimated coefficients were compared under cooperating and conflicting conditions, between the subject groups (CI vs. NH), and under full-spectrum and spectrally degraded conditions for NH listeners. The results indicated that CI listeners’ intonation recognition was enhanced by F0 contour and intensity cues being cooperating, but was adversely affected by these cues being conflicting. On the other hand, with full-spectrum stimuli, NH listeners’ intonation recognition was not affected by cues being cooperating or conflicting. The effects of cues being cooperating or conflicting were comparable between the CI group and NH listeners with spectrally-degraded stimuli. These findings suggest the importance of taking multiple acoustic sources for speech recognition into consideration in aural rehabilitation for CI recipients. PMID:19372651

Study of environmental sound source identification based on hidden Markov model for robust speech recognition

NASA Astrophysics Data System (ADS)

Nishiura, Takanobu; Nakamura, Satoshi

2003-10-01

Humans communicate with each other through speech by focusing on the target speech among environmental sounds in real acoustic environments. We can easily identify the target sound from other environmental sounds. For hands-free speech recognition, the identification of the target speech from environmental sounds is imperative. This mechanism may also be important for a self-moving robot to sense the acoustic environments and communicate with humans. Therefore, this paper first proposes hidden Markov model (HMM)-based environmental sound source identification. Environmental sounds are modeled by three states of HMMs and evaluated using 92 kinds of environmental sounds. The identification accuracy was 95.4%. This paper also proposes a new HMM composition method that composes speech HMMs and an HMM of categorized environmental sounds for robust environmental sound-added speech recognition. As a result of the evaluation experiments, we confirmed that the proposed HMM composition outperforms the conventional HMM composition with speech HMMs and a noise (environmental sound) HMM trained using noise periods prior to the target speech in a captured signal. [Work supported by Ministry of Public Management, Home Affairs, Posts and Telecommunications of Japan.

Speech therapy and voice recognition instrument

NASA Technical Reports Server (NTRS)

Cohen, J.; Babcock, M. L.

1972-01-01

Characteristics of electronic circuit for examining variations in vocal excitation for diagnostic purposes and in speech recognition for determiniog voice patterns and pitch changes are described. Operation of the circuit is discussed and circuit diagram is provided.

Auditory and cognitive factors underlying individual differences in aided speech-understanding among older adults

PubMed Central

Humes, Larry E.; Kidd, Gary R.; Lentz, Jennifer J.

2013-01-01

This study was designed to address individual differences in aided speech understanding among a relatively large group of older adults. The group of older adults consisted of 98 adults (50 female and 48 male) ranging in age from 60 to 86 (mean = 69.2). Hearing loss was typical for this age group and about 90% had not worn hearing aids. All subjects completed a battery of tests, including cognitive (6 measures), psychophysical (17 measures), and speech-understanding (9 measures), as well as the Speech, Spatial, and Qualities of Hearing (SSQ) self-report scale. Most of the speech-understanding measures made use of competing speech and the non-speech psychophysical measures were designed to tap phenomena thought to be relevant for the perception of speech in competing speech (e.g., stream segregation, modulation-detection interference). All measures of speech understanding were administered with spectral shaping applied to the speech stimuli to fully restore audibility through at least 4000 Hz. The measures used were demonstrated to be reliable in older adults and, when compared to a reference group of 28 young normal-hearing adults, age-group differences were observed on many of the measures. Principal-components factor analysis was applied successfully to reduce the number of independent and dependent (speech understanding) measures for a multiple-regression analysis. Doing so yielded one global cognitive-processing factor and five non-speech psychoacoustic factors (hearing loss, dichotic signal detection, multi-burst masking, stream segregation, and modulation detection) as potential predictors. To this set of six potential predictor variables were added subject age, Environmental Sound Identification (ESI), and performance on the text-recognition-threshold (TRT) task (a visual analog of interrupted speech recognition). These variables were used to successfully predict one global aided speech-understanding factor, accounting for about 60% of the variance. PMID:24098273

Intonation and dialog context as constraints for speech recognition.

PubMed

Taylor, P; King, S; Isard, S; Wright, H

1998-01-01

This paper describes a way of using intonation and dialog context to improve the performance of an automatic speech recognition (ASR) system. Our experiments were run on the DCIEM Maptask corpus, a corpus of spontaneous task-oriented dialog speech. This corpus has been tagged according to a dialog analysis scheme that assigns each utterance to one of 12 "move types," such as "acknowledge," "query-yes/no" or "instruct." Most ASR systems use a bigram language model to constrain the possible sequences of words that might be recognized. Here we use a separate bigram language model for each move type. We show that when the "correct" move-specific language model is used for each utterance in the test set, the word error rate of the recognizer drops. Of course when the recognizer is run on previously unseen data, it cannot know in advance what move type the speaker has just produced. To determine the move type we use an intonation model combined with a dialog model that puts constraints on possible sequences of move types, as well as the speech recognizer likelihoods for the different move-specific models. In the full recognition system, the combination of automatic move type recognition with the move specific language models reduces the overall word error rate by a small but significant amount when compared with a baseline system that does not take intonation or dialog acts into account. Interestingly, the word error improvement is restricted to "initiating" move types, where word recognition is important. In "response" move types, where the important information is conveyed by the move type itself--for example, positive versus negative response--there is no word error improvement, but recognition of the response types themselves is good. The paper discusses the intonation model, the language models, and the dialog model in detail and describes the architecture in which they are combined.

Evaluation of auditory functions for Royal Canadian Mounted Police officers.

PubMed

Vaillancourt, Véronique; Laroche, Chantal; Giguère, Christian; Beaulieu, Marc-André; Legault, Jean-Pierre

2011-06-01

Auditory fitness for duty (AFFD) testing is an important element in an assessment of workers' ability to perform job tasks safely and effectively. Functional hearing is particularly critical to job performance in law enforcement. Most often, assessment is based on pure-tone detection thresholds; however, its validity can be questioned and challenged in court. In an attempt to move beyond the pure-tone audiogram, some organizations like the Royal Canadian Mounted Police (RCMP) are incorporating additional testing to supplement audiometric data in their AFFD protocols, such as measurements of speech recognition in quiet and/or in noise, and sound localization. This article reports on the assessment of RCMP officers wearing hearing aids in speech recognition and sound localization tasks. The purpose was to quantify individual performance in different domains of hearing identified as necessary components of fitness for duty, and to document the type of hearing aids prescribed in the field and their benefit for functional hearing. The data are to help RCMP in making more informed decisions regarding AFFD in officers wearing hearing aids. The proposed new AFFD protocol included unaided and aided measures of speech recognition in quiet and in noise using the Hearing in Noise Test (HINT) and sound localization in the left/right (L/R) and front/back (F/B) horizontal planes. Sixty-four officers were identified and selected by the RCMP to take part in this study on the basis of hearing thresholds exceeding current audiometrically based criteria. This article reports the results of 57 officers wearing hearing aids. Based on individual results, 49% of officers were reclassified from nonoperational status to operational with limitations on fine hearing duties, given their unaided and/or aided performance. Group data revealed that hearing aids (1) improved speech recognition thresholds on the HINT, the effects being most prominent in Quiet and in conditions of spatial separation between target and noise (Noise Right and Noise Left) and least considerable in Noise Front; (2) neither significantly improved nor impeded L/R localization; and (3) substantially increased F/B errors in localization in a number of cases. Additional analyses also pointed to the poor ability of threshold data to predict functional abilities for speech in noise (r² = 0.26 to 0.33) and sound localization (r² = 0.03 to 0.28). Only speech in quiet (r² = 0.68 to 0.85) is predicted adequately from threshold data. Combined with previous findings, results indicate that the use of hearing aids can considerably affect F/B localization abilities in a number of individuals. Moreover, speech understanding in noise and sound localization abilities were poorly predicted from pure-tone thresholds, demonstrating the need to specifically test these abilities, both unaided and aided, when assessing AFFD. Finally, further work is needed to develop empirically based hearing criteria for the RCMP and identify best practices in hearing aid fittings for optimal functional hearing abilities. American Academy of Audiology.

Words from spontaneous conversational speech can be recognized with human-like accuracy by an error-driven learning algorithm that discriminates between meanings straight from smart acoustic features, bypassing the phoneme as recognition unit.

PubMed

Arnold, Denis; Tomaschek, Fabian; Sering, Konstantin; Lopez, Florence; Baayen, R Harald

2017-01-01

Sound units play a pivotal role in cognitive models of auditory comprehension. The general consensus is that during perception listeners break down speech into auditory words and subsequently phones. Indeed, cognitive speech recognition is typically taken to be computationally intractable without phones. Here we present a computational model trained on 20 hours of conversational speech that recognizes word meanings within the range of human performance (model 25%, native speakers 20-44%), without making use of phone or word form representations. Our model also generates successfully predictions about the speed and accuracy of human auditory comprehension. At the heart of the model is a 'wide' yet sparse two-layer artificial neural network with some hundred thousand input units representing summaries of changes in acoustic frequency bands, and proxies for lexical meanings as output units. We believe that our model holds promise for resolving longstanding theoretical problems surrounding the notion of the phone in linguistic theory.

Effect of motion on speech recognition.

PubMed

Davis, Timothy J; Grantham, D Wesley; Gifford, René H

2016-07-01

The benefit of spatial separation for talkers in a multi-talker environment is well documented. However, few studies have examined the effect of talker motion on speech recognition. In the current study, we evaluated the effects of (1) motion of the target or distracters, (2) a priori information about the target and distracter spatial configurations, and (3) target and distracter location. In total, seventeen young adults with normal hearing were tested in a large anechoic chamber in two experiments. In Experiment 1, seven stimulus conditions were tested using the Coordinate Response Measure (Bolia et al., 2000) speech corpus, in which subjects were required to report the key words in a target sentence presented simultaneously with two distracter sentences. As in previous studies, there was a significant improvement in key word identification for conditions in which the target and distracters were spatially separated as compared to the co-located conditions. In addition, 1) motion of either talker or distracter resulted in improved performance compared to stationary presentation (talker motion yielded significantly better performance than distracter motion) 2) a priori information regarding stimulus configuration was not beneficial, and 3) performance was significantly better with key words at 0° azimuth as compared to -60° (on the listener's left). Experiment 2 included two additional conditions designed to assess whether the benefit of motion observed in Experiment 1 was due to the motion itself or to the fact that the motion conditions introduced small spatial separations in the target and distracter key words. Results showed that small spatial separations (on the order of 5-8°) resulted in improved performance (relative to co-located key words) whether the sentences were moving or stationary. These results suggest that in the presence of distracting messages, motion of either target or distracters and/or small spatial separation of the key words may be beneficial for sound source segregation and thus for improved speech recognition. Copyright © 2016 Elsevier B.V. All rights reserved.

Effects of Noise Level and Cognitive Function on Speech Perception in Normal Elderly and Elderly with Amnestic Mild Cognitive Impairment.

PubMed

Lee, Soo Jung; Park, Kyung Won; Kim, Lee-Suk; Kim, HyangHee

2016-06-01

Along with auditory function, cognitive function contributes to speech perception in the presence of background noise. Older adults with cognitive impairment might, therefore, have more difficulty perceiving speech-in-noise than their peers who have normal cognitive function. We compared the effects of noise level and cognitive function on speech perception in patients with amnestic mild cognitive impairment (aMCI), cognitively normal older adults, and cognitively normal younger adults. We studied 14 patients with aMCI and 14 age-, education-, and hearing threshold-matched cognitively intact older adults as experimental groups, and 14 younger adults as a control group. We assessed speech perception with monosyllabic word and sentence recognition tests at four noise levels: quiet condition and signal-to-noise ratio +5 dB, 0 dB, and -5 dB. We also evaluated the aMCI group with a neuropsychological assessment. Controlling for hearing thresholds, we found that the aMCI group scored significantly lower than both the older adults and the younger adults only when the noise level was high (signal-to-noise ratio -5 dB). At signal-to-noise ratio -5 dB, both older groups had significantly lower scores than the younger adults on the sentence recognition test. The aMCI group's sentence recognition performance was related to their executive function scores. Our findings suggest that patients with aMCI have more problems communicating in noisy situations in daily life than do their cognitively healthy peers and that older listeners with more difficulties understanding speech in noise should be considered for testing of neuropsychological function as well as hearing.

Noise Suppression Based on Multi-Model Compositions Using Multi-Pass Search with Multi-Label N-gram Models

NASA Astrophysics Data System (ADS)

Jitsuhiro, Takatoshi; Toriyama, Tomoji; Kogure, Kiyoshi

We propose a noise suppression method based on multi-model compositions and multi-pass search. In real environments, input speech for speech recognition includes many kinds of noise signals. To obtain good recognized candidates, suppressing many kinds of noise signals at once and finding target speech is important. Before noise suppression, to find speech and noise label sequences, we introduce multi-pass search with acoustic models including many kinds of noise models and their compositions, their n-gram models, and their lexicon. Noise suppression is frame-synchronously performed using the multiple models selected by recognized label sequences with time alignments. We evaluated this method using the E-Nightingale task, which contains voice memoranda spoken by nurses during actual work at hospitals. The proposed method obtained higher performance than the conventional method.

The pupil response is sensitive to divided attention during speech processing.

PubMed

Koelewijn, Thomas; Shinn-Cunningham, Barbara G; Zekveld, Adriana A; Kramer, Sophia E

2014-06-01

Dividing attention over two streams of speech strongly decreases performance compared to focusing on only one. How divided attention affects cognitive processing load as indexed with pupillometry during speech recognition has so far not been investigated. In 12 young adults the pupil response was recorded while they focused on either one or both of two sentences that were presented dichotically and masked by fluctuating noise across a range of signal-to-noise ratios. In line with previous studies, the performance decreases when processing two target sentences instead of one. Additionally, dividing attention to process two sentences caused larger pupil dilation and later peak pupil latency than processing only one. This suggests an effect of attention on cognitive processing load (pupil dilation) during speech processing in noise. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Experimental investigation of the effects of the acoustical conditions in a simulated classroom on speech recognition and learning in children a

PubMed Central

Valente, Daniel L.; Plevinsky, Hallie M.; Franco, John M.; Heinrichs-Graham, Elizabeth C.; Lewis, Dawna E.

2012-01-01

The potential effects of acoustical environment on speech understanding are especially important as children enter school where students’ ability to hear and understand complex verbal information is critical to learning. However, this ability is compromised because of widely varied and unfavorable classroom acoustics. The extent to which unfavorable classroom acoustics affect children’s performance on longer learning tasks is largely unknown as most research has focused on testing children using words, syllables, or sentences as stimuli. In the current study, a simulated classroom environment was used to measure comprehension performance of two classroom learning activities: a discussion and lecture. Comprehension performance was measured for groups of elementary-aged students in one of four environments with varied reverberation times and background noise levels. The reverberation time was either 0.6 or 1.5 s, and the signal-to-noise level was either +10 or +7 dB. Performance is compared to adult subjects as well as to sentence-recognition in the same condition. Significant differences were seen in comprehension scores as a function of age and condition; both increasing background noise and reverberation degraded performance in comprehension tasks compared to minimal differences in measures of sentence-recognition. PMID:22280587

Multilevel Analysis in Analyzing Speech Data

ERIC Educational Resources Information Center

Guddattu, Vasudeva; Krishna, Y.

2011-01-01

The speech produced by human vocal tract is a complex acoustic signal, with diverse applications in phonetics, speech synthesis, automatic speech recognition, speaker identification, communication aids, speech pathology, speech perception, machine translation, hearing research, rehabilitation and assessment of communication disorders and many…

A Development of a System Enables Character Input and PC Operation via Voice for a Physically Disabled Person with a Speech Impediment

NASA Astrophysics Data System (ADS)

Tanioka, Toshimasa; Egashira, Hiroyuki; Takata, Mayumi; Okazaki, Yasuhisa; Watanabe, Kenzi; Kondo, Hiroki

We have designed and implemented a PC operation support system for a physically disabled person with a speech impediment via voice. Voice operation is an effective method for a physically disabled person with involuntary movement of the limbs and the head. We have applied a commercial speech recognition engine to develop our system for practical purposes. Adoption of a commercial engine reduces development cost and will contribute to make our system useful to another speech impediment people. We have customized commercial speech recognition engine so that it can recognize the utterance of a person with a speech impediment. We have restricted the words that the recognition engine recognizes and separated a target words from similar words in pronunciation to avoid misrecognition. Huge number of words registered in commercial speech recognition engines cause frequent misrecognition for speech impediments' utterance, because their utterance is not clear and unstable. We have solved this problem by narrowing the choice of input down in a small number and also by registering their ambiguous pronunciations in addition to the original ones. To realize all character inputs and all PC operation with a small number of words, we have designed multiple input modes with categorized dictionaries and have introduced two-step input in each mode except numeral input to enable correct operation with small number of words. The system we have developed is in practical level. The first author of this paper is physically disabled with a speech impediment. He has been able not only character input into PC but also to operate Windows system smoothly by using this system. He uses this system in his daily life. This paper is written by him with this system. At present, the speech recognition is customized to him. It is, however, possible to customize for other users by changing words and registering new pronunciation according to each user's utterance.

Use of Adaptive Digital Signal Processing to Improve Speech Communication for Normally Hearing aand Hearing-Impaired Subjects.

ERIC Educational Resources Information Center

Harris, Richard W.; And Others

1988-01-01

A two-microphone adaptive digital noise cancellation technique improved word-recognition ability for 20 normal and 12 hearing-impaired adults by reducing multitalker speech babble and speech spectrum noise 18-22 dB. Word recognition improvements averaged 37-50 percent for normal and 27-40 percent for hearing-impaired subjects. Improvement was best…

An Exploration of the Potential of Automatic Speech Recognition to Assist and Enable Receptive Communication in Higher Education

ERIC Educational Resources Information Center

Wald, Mike

2006-01-01

The potential use of Automatic Speech Recognition to assist receptive communication is explored. The opportunities and challenges that this technology presents students and staff to provide captioning of speech online or in classrooms for deaf or hard of hearing students and assist blind, visually impaired or dyslexic learners to read and search…

Effects of Electrical Stimulation Rate on Speech Recognition in Cochlear Implant Users

PubMed Central

Park, Sung Hye; Kim, Eunoak; Lee, Hyo-Jeong

2012-01-01

Background and Objectives The stimulus signals delivered in cochlear implant (CI) systems are generally derived by sampling the temporal envelope of each channel at some constant rate and using its intensity to control the stimulation current level delivered to the corresponding electrode site. The objective of the study was to investigate speech recognition performance of cochlear implant users in quiet and noisy environments using either moderate or high rates of electrical stimulations. Materials and Methods Six post-lingually deafened adult users of the Nucleus CI24 cochlear implant (Contour® electrode array, Cochlear™, Macquarie Park, Australia) with the Freedom® speech processor participated in the study. Stimulation rates of 900 and 2400 pulses-per-second/channel (pps/ch) were used after both stimulation programs were balanced for loudness. Monosyllabic word and sentence recognition scores in quiet and noisy environments were evaluated for each stimulation program after two months of practice. Subjects were also asked to respond to a questionnaire to examine their preference to any stimulation rate in different hearing conditions. Results Word recognition scores for monosyllabic words in quiet conditions with the 900 stimulation rate was better than that of the 2400 stimulation rate, although no significant differences between them were found for sentence test in noise. A survey questionnaire indicated that most subjects preferred the 900 stimulation rate to the 2400 stimulation rate, especially in quiet conditions. Conclusions Most subjects indicated a preference for 900 pps/ch rate in quiet conditions. It is recommended to remap at 900 pps/ch for those CI users whose performance in quiet conditions is less than ideal. PMID:24653862

Effects of electrical stimulation rate on speech recognition in cochlear implant users.

PubMed

Park, Sung Hye; Kim, Eunoak; Lee, Hyo-Jeong; Kim, Hyung-Jong

2012-04-01

The stimulus signals delivered in cochlear implant (CI) systems are generally derived by sampling the temporal envelope of each channel at some constant rate and using its intensity to control the stimulation current level delivered to the corresponding electrode site. The objective of the study was to investigate speech recognition performance of cochlear implant users in quiet and noisy environments using either moderate or high rates of electrical stimulations. Six post-lingually deafened adult users of the Nucleus CI24 cochlear implant (Contour® electrode array, Cochlear™, Macquarie Park, Australia) with the Freedom® speech processor participated in the study. Stimulation rates of 900 and 2400 pulses-per-second/channel (pps/ch) were used after both stimulation programs were balanced for loudness. Monosyllabic word and sentence recognition scores in quiet and noisy environments were evaluated for each stimulation program after two months of practice. Subjects were also asked to respond to a questionnaire to examine their preference to any stimulation rate in different hearing conditions. Word recognition scores for monosyllabic words in quiet conditions with the 900 stimulation rate was better than that of the 2400 stimulation rate, although no significant differences between them were found for sentence test in noise. A survey questionnaire indicated that most subjects preferred the 900 stimulation rate to the 2400 stimulation rate, especially in quiet conditions. Most subjects indicated a preference for 900 pps/ch rate in quiet conditions. It is recommended to remap at 900 pps/ch for those CI users whose performance in quiet conditions is less than ideal.

Assessing the Importance of Lexical Tone Contour to Sentence Perception in Mandarin-Speaking Children With Normal Hearing.

PubMed

Zhu, Shufeng; Wong, Lena L N; Wang, Bin; Chen, Fei

2017-07-12

The aim of the present study was to evaluate the influence of lexical tone contour and age on sentence perception in quiet and in noise conditions in Mandarin-speaking children ages 7 to 11 years with normal hearing. Test materials were synthesized Mandarin sentences, each word with a manipulated lexical contour, that is, normal contour, flat contour, or a tone contour randomly selected from the four Mandarin lexical tone contours. A convenience sample of 75 Mandarin-speaking participants with normal hearing, ages 7, 9, and 11 years (25 participants in each age group), was selected. Participants were asked to repeat the synthesized speech in quiet and in speech spectrum-shaped noise at 0 dB signal-to-noise ratio. In quiet, sentence recognition by the 11-year-old children was similar to that of adults, and misrepresented lexical tone contours did not have a detrimental effect. However, the performance of children ages 9 and 7 years was significantly poorer. The performance of all three age groups, especially the younger children, declined significantly in noise. The present research suggests that lexical tone contour plays an important role in Mandarin sentence recognition, and misrepresented tone contours result in greater difficulty in sentence recognition in younger children. These results imply that maturation and/or language use experience play a role in the processing of tone contours for Mandarin speech understanding, particularly in noise.

Speech recognition-based and automaticity programs to help students with severe reading and spelling problems.

PubMed

Higgins, Eleanor L; Raskind, Marshall H

2004-12-01

This study was conducted to assess the effectiveness of two programs developed by the Frostig Center Research Department to improve the reading and spelling of students with learning disabilities (LD): a computer Speech Recognition-based Program (SRBP) and a computer and text-based Automaticity Program (AP). Twenty-eight LD students with reading and spelling difficulties (aged 8 to 18) received each program for 17 weeks and were compared with 16 students in a contrast group who did not receive either program. After adjusting for age and IQ, both the SRBP and AP groups showed significant differences over the contrast group in improving word recognition and reading comprehension. Neither program showed significant differences over contrasts in spelling. The SRBP also improved the performance of the target group when compared with the contrast group on phonological elision and nonword reading efficiency tasks. The AP showed significant differences in all process and reading efficiency measures.

The Impact of Age, Background Noise, Semantic Ambiguity, and Hearing Loss on Recognition Memory for Spoken Sentences.

PubMed

Koeritzer, Margaret A; Rogers, Chad S; Van Engen, Kristin J; Peelle, Jonathan E

2018-03-15

The goal of this study was to determine how background noise, linguistic properties of spoken sentences, and listener abilities (hearing sensitivity and verbal working memory) affect cognitive demand during auditory sentence comprehension. We tested 30 young adults and 30 older adults. Participants heard lists of sentences in quiet and in 8-talker babble at signal-to-noise ratios of +15 dB and +5 dB, which increased acoustic challenge but left the speech largely intelligible. Half of the sentences contained semantically ambiguous words to additionally manipulate cognitive challenge. Following each list, participants performed a visual recognition memory task in which they viewed written sentences and indicated whether they remembered hearing the sentence previously. Recognition memory (indexed by d') was poorer for acoustically challenging sentences, poorer for sentences containing ambiguous words, and differentially poorer for noisy high-ambiguity sentences. Similar patterns were observed for Z-transformed response time data. There were no main effects of age, but age interacted with both acoustic clarity and semantic ambiguity such that older adults' recognition memory was poorer for acoustically degraded high-ambiguity sentences than the young adults'. Within the older adult group, exploratory correlation analyses suggested that poorer hearing ability was associated with poorer recognition memory for sentences in noise, and better verbal working memory was associated with better recognition memory for sentences in noise. Our results demonstrate listeners' reliance on domain-general cognitive processes when listening to acoustically challenging speech, even when speech is highly intelligible. Acoustic challenge and semantic ambiguity both reduce the accuracy of listeners' recognition memory for spoken sentences. https://doi.org/10.23641/asha.5848059.

Relationships between Structural and Acoustic Properties of Maternal Talk and Children's Early Word Recognition

ERIC Educational Resources Information Center

Suttora, Chiara; Salerni, Nicoletta; Zanchi, Paola; Zampini, Laura; Spinelli, Maria; Fasolo, Mirco

2017-01-01

This study aimed to investigate specific associations between structural and acoustic characteristics of infant-directed (ID) speech and word recognition. Thirty Italian-acquiring children and their mothers were tested when the children were 1;3. Children's word recognition was measured with the looking-while-listening task. Maternal ID speech was…

Speech Recognition in Adults with Cochlear Implants: The Effects of Working Memory, Phonological Sensitivity, and Aging

ERIC Educational Resources Information Center

Moberly, Aaron C.; Harris, Michael S.; Boyce, Lauren; Nittrouer, Susan

2017-01-01

Purpose: Models of speech recognition suggest that "top-down" linguistic and cognitive functions, such as use of phonotactic constraints and working memory, facilitate recognition under conditions of degradation, such as in noise. The question addressed in this study was what happens to these functions when a listener who has experienced…

The Effect of Asymmetrical Signal Degradation on Binaural Speech Recognition in Children and Adults.

ERIC Educational Resources Information Center

Rothpletz, Ann M.; Tharpe, Anne Marie; Grantham, D. Wesley

2004-01-01

To determine the effect of asymmetrical signal degradation on binaural speech recognition, 28 children and 14 adults were administered a sentence recognition task amidst multitalker babble. There were 3 listening conditions: (a) monaural, with mild degradation in 1 ear; (b) binaural, with mild degradation in both ears (symmetric degradation); and…

Learning Models and Real-Time Speech Recognition.

ERIC Educational Resources Information Center

Danforth, Douglas G.; And Others

This report describes the construction and testing of two "psychological" learning models for the purpose of computer recognition of human speech over the telephone. One of the two models was found to be superior in all tests. A regression analysis yielded a 92.3% recognition rate for 14 subjects ranging in age from 6 to 13 years. Tests…

Use of Authentic-Speech Technique for Teaching Sound Recognition to EFL Students

ERIC Educational Resources Information Center

Sersen, William J.

2011-01-01

The main objective of this research was to test an authentic-speech technique for improving the sound-recognition skills of EFL (English as a foreign language) students at Roi-Et Rajabhat University. The secondary objective was to determine the correlation, if any, between students' self-evaluation of sound-recognition progress and the actual…

What happens to the motor theory of perception when the motor system is damaged?

PubMed

Stasenko, Alena; Garcea, Frank E; Mahon, Bradford Z

2013-09-01

Motor theories of perception posit that motor information is necessary for successful recognition of actions. Perhaps the most well known of this class of proposals is the motor theory of speech perception, which argues that speech recognition is fundamentally a process of identifying the articulatory gestures (i.e. motor representations) that were used to produce the speech signal. Here we review neuropsychological evidence from patients with damage to the motor system, in the context of motor theories of perception applied to both manual actions and speech. Motor theories of perception predict that patients with motor impairments will have impairments for action recognition. Contrary to that prediction, the available neuropsychological evidence indicates that recognition can be spared despite profound impairments to production. These data falsify strong forms of the motor theory of perception, and frame new questions about the dynamical interactions that govern how information is exchanged between input and output systems.

What happens to the motor theory of perception when the motor system is damaged?

PubMed Central

Stasenko, Alena; Garcea, Frank E.; Mahon, Bradford Z.

2016-01-01

Motor theories of perception posit that motor information is necessary for successful recognition of actions. Perhaps the most well known of this class of proposals is the motor theory of speech perception, which argues that speech recognition is fundamentally a process of identifying the articulatory gestures (i.e. motor representations) that were used to produce the speech signal. Here we review neuropsychological evidence from patients with damage to the motor system, in the context of motor theories of perception applied to both manual actions and speech. Motor theories of perception predict that patients with motor impairments will have impairments for action recognition. Contrary to that prediction, the available neuropsychological evidence indicates that recognition can be spared despite profound impairments to production. These data falsify strong forms of the motor theory of perception, and frame new questions about the dynamical interactions that govern how information is exchanged between input and output systems. PMID:26823687

Sentence Recognition Prediction for Hearing-impaired Listeners in Stationary and Fluctuation Noise With FADE

PubMed Central

Schädler, Marc René; Warzybok, Anna; Meyer, Bernd T.; Brand, Thomas

2016-01-01

To characterize the individual patient’s hearing impairment as obtained with the matrix sentence recognition test, a simulation Framework for Auditory Discrimination Experiments (FADE) is extended here using the Attenuation and Distortion (A+D) approach by Plomp as a blueprint for setting the individual processing parameters. FADE has been shown to predict the outcome of both speech recognition tests and psychoacoustic experiments based on simulations using an automatic speech recognition system requiring only few assumptions. It builds on the closed-set matrix sentence recognition test which is advantageous for testing individual speech recognition in a way comparable across languages. Individual predictions of speech recognition thresholds in stationary and in fluctuating noise were derived using the audiogram and an estimate of the internal level uncertainty for modeling the individual Plomp curves fitted to the data with the Attenuation (A-) and Distortion (D-) parameters of the Plomp approach. The “typical” audiogram shapes from Bisgaard et al with or without a “typical” level uncertainty and the individual data were used for individual predictions. As a result, the individualization of the level uncertainty was found to be more important than the exact shape of the individual audiogram to accurately model the outcome of the German Matrix test in stationary or fluctuating noise for listeners with hearing impairment. The prediction accuracy of the individualized approach also outperforms the (modified) Speech Intelligibility Index approach which is based on the individual threshold data only. PMID:27604782

The effects of digital signal processing features on children's speech recognition and loudness perception.

PubMed

Crukley, Jeffery; Scollie, Susan D

2014-03-01

The purpose of this study was to determine the effects of hearing instruments set to Desired Sensation Level version 5 (DSL v5) hearing instrument prescription algorithm targets and equipped with directional microphones and digital noise reduction (DNR) on children's sentence recognition in noise performance and loudness perception in a classroom environment. Ten children (ages 8-17 years) with stable, congenital sensorineural hearing losses participated in the study. Participants were fitted bilaterally with behind-the-ear hearing instruments set to DSL v5 prescriptive targets. Sentence recognition in noise was evaluated using the Bamford-Kowal-Bench Speech in Noise Test (Niquette et al., 2003). Loudness perception was evaluated using a modified version of the Contour Test of Loudness Perception (Cox, Alexander, Taylor, & Gray, 1997). Children's sentence recognition in noise performance was significantly better when using directional microphones alone or in combination with DNR than when using omnidirectional microphones alone or in combination with DNR. Children's loudness ratings for sounds above 72 dB SPL were lowest when fitted with the DSL v5 Noise prescription combined with directional microphones. DNR use showed no effect on loudness ratings. Use of the DSL v5 Noise prescription with a directional microphone improved sentence recognition in noise performance and reduced loudness perception ratings for loud sounds relative to a typical clinical reference fitting with the DSL v5 Quiet prescription with no digital signal processing features enabled. Potential clinical strategies are discussed.

Personal FM systems for children with autism spectrum disorders (ASD) and/or attention-deficit hyperactivity disorder (ADHD): an initial investigation.

PubMed

Schafer, Erin C; Mathews, Lauren; Mehta, Smita; Hill, Margaret; Munoz, Ashley; Bishop, Rachel; Moloney, Molly

2013-01-01

The goal of this initial investigation was to examine the potential benefit of a frequency modulation (FM) system for 11 children diagnosed with autism spectrum disorders (ASD), attention-deficit hyperactivity disorder (ADHD), or both disorders through measures of speech recognition performance in noise, observed classroom behavior, and teacher-rated educational risk and listening behaviors. Use of the FM system resulted in significant average improvements in speech recognition in noise for the children with ASD and ADHD as well as large effect sizes. When compared to typically functioning peers, children with ASD and ADHD had significantly poorer average speech recognition performance in noise without the FM system but comparable average performance when the FM system was used. Similarly, classroom observations yielded a significant increase in on-task behaviors and large effect sizes when the FM system was in use during two separate trial periods. Although teacher ratings on questionnaires showed no significant improvement in the average level of educational risk of participants, they did indicate significant improvement in average listening behaviors during two trial periods with the FM system. Given the significantly better speech recognition in noise, increased on-task behaviors, and improved teacher ratings of listening behaviors with the FM system, these devices may be a viable option for children who have ASD and ADHD in the classroom. However, an individual evaluation including audiological testing and a functional evaluation in the child's primary learning environment will be necessary to determine the benefit of an FM system for a particular student. 1. The reader will be able to describe the potential benefit of FM systems for children with ASD and/or ADHD. 2. The reader will be able to identify on-task versus off-task listening behaviors in children with ASD and/or ADHD. 3. The reader will be able to explain the components of a successful pre-fit education program that may be necessary prior to fitting an FM system in children with ASD. Copyright © 2012 Elsevier Inc. All rights reserved.

Blind speech separation system for humanoid robot with FastICA for audio filtering and separation

NASA Astrophysics Data System (ADS)

Budiharto, Widodo; Santoso Gunawan, Alexander Agung

2016-07-01

Nowadays, there are many developments in building intelligent humanoid robot, mainly in order to handle voice and image. In this research, we propose blind speech separation system using FastICA for audio filtering and separation that can be used in education or entertainment. Our main problem is to separate the multi speech sources and also to filter irrelevant noises. After speech separation step, the results will be integrated with our previous speech and face recognition system which is based on Bioloid GP robot and Raspberry Pi 2 as controller. The experimental results show the accuracy of our blind speech separation system is about 88% in command and query recognition cases.

New Ideas for Speech Recognition and Related Technologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holzrichter, J F

The ideas relating to the use of organ motion sensors for the purposes of speech recognition were first described by.the author in spring 1994. During the past year, a series of productive collaborations between the author, Tom McEwan and Larry Ng ensued and have lead to demonstrations, new sensor ideas, and algorithmic descriptions of a large number of speech recognition concepts. This document summarizes the basic concepts of recognizing speech once organ motions have been obtained. Micro power radars and their uses for the measurement of body organ motions, such as those of the heart and lungs, have been demonstratedmore » by Tom McEwan over the past two years. McEwan and I conducted a series of experiments, using these instruments, on vocal organ motions beginning in late spring, during which we observed motions of vocal folds (i.e., cords), tongue, jaw, and related organs that are very useful for speech recognition and other purposes. These will be reviewed in a separate paper. Since late summer 1994, Lawrence Ng and I have worked to make many of the initial recognition ideas more rigorous and to investigate the applications of these new ideas to new speech recognition algorithms, to speech coding, and to speech synthesis. I introduce some of those ideas in section IV of this document, and we describe them more completely in the document following this one, UCRL-UR-120311. For the design and operation of micro-power radars and their application to body organ motions, the reader may contact Tom McEwan directly. The capability for using EM sensors (i.e., radar units) to measure body organ motions and positions has been available for decades. Impediments to their use appear to have been size, excessive power, lack of resolution, and lack of understanding of the value of organ motion measurements, especially as applied to speech related technologies. However, with the invention of very low power, portable systems as demonstrated by McEwan at LLNL researchers have begun to think differently about practical applications of such radars. In particular, his demonstrations of heart and lung motions have opened up many new areas of application for human and animal measurements.« less

Human phoneme recognition depending on speech-intrinsic variability.

PubMed

Meyer, Bernd T; Jürgens, Tim; Wesker, Thorsten; Brand, Thomas; Kollmeier, Birger

2010-11-01

The influence of different sources of speech-intrinsic variation (speaking rate, effort, style and dialect or accent) on human speech perception was investigated. In listening experiments with 16 listeners, confusions of consonant-vowel-consonant (CVC) and vowel-consonant-vowel (VCV) sounds in speech-weighted noise were analyzed. Experiments were based on the OLLO logatome speech database, which was designed for a man-machine comparison. It contains utterances spoken by 50 speakers from five dialect/accent regions and covers several intrinsic variations. By comparing results depending on intrinsic and extrinsic variations (i.e., different levels of masking noise), the degradation induced by variabilities can be expressed in terms of the SNR. The spectral level distance between the respective speech segment and the long-term spectrum of the masking noise was found to be a good predictor for recognition rates, while phoneme confusions were influenced by the distance to spectrally close phonemes. An analysis based on transmitted information of articulatory features showed that voicing and manner of articulation are comparatively robust cues in the presence of intrinsic variations, whereas the coding of place is more degraded. The database and detailed results have been made available for comparisons between human speech recognition (HSR) and automatic speech recognizers (ASR).

A measure for assessing the effects of audiovisual speech integration.

PubMed

Altieri, Nicholas; Townsend, James T; Wenger, Michael J

2014-06-01

We propose a measure of audiovisual speech integration that takes into account accuracy and response times. This measure should prove beneficial for researchers investigating multisensory speech recognition, since it relates to normal-hearing and aging populations. As an example, age-related sensory decline influences both the rate at which one processes information and the ability to utilize cues from different sensory modalities. Our function assesses integration when both auditory and visual information are available, by comparing performance on these audiovisual trials with theoretical predictions for performance under the assumptions of parallel, independent self-terminating processing of single-modality inputs. We provide example data from an audiovisual identification experiment and discuss applications for measuring audiovisual integration skills across the life span.

Internship Abstract and Final Reflection

NASA Technical Reports Server (NTRS)

Sandor, Edward

2016-01-01

The primary objective for this internship is the evaluation of an embedded natural language processor (NLP) as a way to introduce voice control into future space suits. An embedded natural language processor would provide an astronaut hands-free control for making adjustments to the environment of the space suit and checking status of consumables procedures and navigation. Additionally, the use of an embedded NLP could potentially reduce crew fatigue, increase the crewmember's situational awareness during extravehicular activity (EVA) and improve the ability to focus on mission critical details. The use of an embedded NLP may be valuable for other human spaceflight applications desiring hands-free control as well. An embedded NLP is unique because it is a small device that performs language tasks, including speech recognition, which normally require powerful processors. The dedicated device could perform speech recognition locally with a smaller form-factor and lower power consumption than traditional methods.

Speech Perception, Word Recognition and the Structure of the Lexicon. Research on Speech Perception Progress Report No. 10.

ERIC Educational Resources Information Center

Pisoni, David B.; And Others

The results of three projects concerned with auditory word recognition and the structure of the lexicon are reported in this paper. The first project described was designed to test experimentally several specific predictions derived from MACS, a simulation model of the Cohort Theory of word recognition. The second project description provides the…

The Development of the Orthographic Consistency Effect in Speech Recognition: From Sublexical to Lexical Involvement

ERIC Educational Resources Information Center

Ventura, Paulo; Morais, Jose; Kolinsky, Regine

2007-01-01

The influence of orthography on children's on-line auditory word recognition was studied from the end of Grade 2 to the end of Grade 4, by examining the orthographic consistency effect [Ziegler, J. C., & Ferrand, L. (1998). Orthography shapes the perception of speech: The consistency effect in auditory recognition. "Psychonomic Bulletin & Review",…

Discriminative analysis of lip motion features for speaker identification and speech-reading.

PubMed

Cetingül, H Ertan; Yemez, Yücel; Erzin, Engin; Tekalp, A Murat

2006-10-01

There have been several studies that jointly use audio, lip intensity, and lip geometry information for speaker identification and speech-reading applications. This paper proposes using explicit lip motion information, instead of or in addition to lip intensity and/or geometry information, for speaker identification and speech-reading within a unified feature selection and discrimination analysis framework, and addresses two important issues: 1) Is using explicit lip motion information useful, and, 2) if so, what are the best lip motion features for these two applications? The best lip motion features for speaker identification are considered to be those that result in the highest discrimination of individual speakers in a population, whereas for speech-reading, the best features are those providing the highest phoneme/word/phrase recognition rate. Several lip motion feature candidates have been considered including dense motion features within a bounding box about the lip, lip contour motion features, and combination of these with lip shape features. Furthermore, a novel two-stage, spatial, and temporal discrimination analysis is introduced to select the best lip motion features for speaker identification and speech-reading applications. Experimental results using an hidden-Markov-model-based recognition system indicate that using explicit lip motion information provides additional performance gains in both applications, and lip motion features prove more valuable in the case of speech-reading application.

Evaluation of speech reception threshold in noise in young Cochlear™ Nucleus® system 6 implant recipients using two different digital remote microphone technologies and a speech enhancement sound processing algorithm.

PubMed

Razza, Sergio; Zaccone, Monica; Meli, Aannalisa; Cristofari, Eliana

2017-12-01

Children affected by hearing loss can experience difficulties in challenging and noisy environments even when deafness is corrected by Cochlear implant (CI) devices. These patients have a selective attention deficit in multiple listening conditions. At present, the most effective ways to improve the performance of speech recognition in noise consists of providing CI processors with noise reduction algorithms and of providing patients with bilateral CIs. The aim of this study was to compare speech performances in noise, across increasing noise levels, in CI recipients using two kinds of wireless remote-microphone radio systems that use digital radio frequency transmission: the Roger Inspiro accessory and the Cochlear Wireless Mini Microphone accessory. Eleven Nucleus Cochlear CP910 CI young user subjects were studied. The signal/noise ratio, at a speech reception threshold (SRT) value of 50%, was measured in different conditions for each patient: with CI only, with the Roger or with the MiniMic accessory. The effect of the application of the SNR-noise reduction algorithm in each of these conditions was also assessed. The tests were performed with the subject positioned in front of the main speaker, at a distance of 2.5 m. Another two speakers were positioned at 3.50 m. The main speaker at 65 dB issued disyllabic words. Babble noise signal was delivered through the other speakers, with variable intensity. The use of both wireless remote microphones improved the SRT results. Both systems improved gain of speech performances. The gain was higher with the Mini Mic system (SRT = -4.76) than the Roger system (SRT = -3.01). The addition of the NR algorithm did not statistically further improve the results. There is significant improvement in speech recognition results with both wireless digital remote microphone accessories, in particular with the Mini Mic system when used with the CP910 processor. The use of a remote microphone accessory surpasses the benefit of application of NR algorithm. Copyright © 2017. Published by Elsevier B.V.

Do What I Say! Voice Recognition Makes Major Advances.

ERIC Educational Resources Information Center

Ruley, C. Dorsey

1994-01-01

Explains voice recognition technology applications in the workplace, schools, and libraries. Highlights include a voice-controlled work station using the DragonDictate system that can be used with dyslexic students, converting text to speech, and converting speech to text. (LRW)

Measuring the effects of spectral smearing and enhancement on speech recognition in noise for adults and children

PubMed Central

Nittrouer, Susan; Tarr, Eric; Wucinich, Taylor; Moberly, Aaron C.; Lowenstein, Joanna H.

2015-01-01

Broadened auditory filters associated with sensorineural hearing loss have clearly been shown to diminish speech recognition in noise for adults, but far less is known about potential effects for children. This study examined speech recognition in noise for adults and children using simulated auditory filters of different widths. Specifically, 5 groups (20 listeners each) of adults or children (5 and 7 yrs), were asked to recognize sentences in speech-shaped noise. Seven-year-olds listened at 0 dB signal-to-noise ratio (SNR) only; 5-yr-olds listened at +3 or 0 dB SNR; and adults listened at 0 or −3 dB SNR. Sentence materials were processed both to smear the speech spectrum (i.e., simulate broadened filters), and to enhance the spectrum (i.e., simulate narrowed filters). Results showed: (1) Spectral smearing diminished recognition for listeners of all ages; (2) spectral enhancement did not improve recognition, and in fact diminished it somewhat; and (3) interactions were observed between smearing and SNR, but only for adults. That interaction made age effects difficult to gauge. Nonetheless, it was concluded that efforts to diagnose the extent of broadening of auditory filters and to develop techniques to correct this condition could benefit patients with hearing loss, especially children. PMID:25920851

The role of spectral and temporal cues in voice gender discrimination by normal-hearing listeners and cochlear implant users.

PubMed

Fu, Qian-Jie; Chinchilla, Sherol; Galvin, John J

2004-09-01

The present study investigated the relative importance of temporal and spectral cues in voice gender discrimination and vowel recognition by normal-hearing subjects listening to an acoustic simulation of cochlear implant speech processing and by cochlear implant users. In the simulation, the number of speech processing channels ranged from 4 to 32, thereby varying the spectral resolution; the cutoff frequencies of the channels' envelope filters ranged from 20 to 320 Hz, thereby manipulating the available temporal cues. For normal-hearing subjects, results showed that both voice gender discrimination and vowel recognition scores improved as the number of spectral channels was increased. When only 4 spectral channels were available, voice gender discrimination significantly improved as the envelope filter cutoff frequency was increased from 20 to 320 Hz. For all spectral conditions, increasing the amount of temporal information had no significant effect on vowel recognition. Both voice gender discrimination and vowel recognition scores were highly variable among implant users. The performance of cochlear implant listeners was similar to that of normal-hearing subjects listening to comparable speech processing (4-8 spectral channels). The results suggest that both spectral and temporal cues contribute to voice gender discrimination and that temporal cues are especially important for cochlear implant users to identify the voice gender when there is reduced spectral resolution.

Classifier Subset Selection for the Stacked Generalization Method Applied to Emotion Recognition in Speech

PubMed Central

Álvarez, Aitor; Sierra, Basilio; Arruti, Andoni; López-Gil, Juan-Miguel; Garay-Vitoria, Nestor

2015-01-01

In this paper, a new supervised classification paradigm, called classifier subset selection for stacked generalization (CSS stacking), is presented to deal with speech emotion recognition. The new approach consists of an improvement of a bi-level multi-classifier system known as stacking generalization by means of an integration of an estimation of distribution algorithm (EDA) in the first layer to select the optimal subset from the standard base classifiers. The good performance of the proposed new paradigm was demonstrated over different configurations and datasets. First, several CSS stacking classifiers were constructed on the RekEmozio dataset, using some specific standard base classifiers and a total of 123 spectral, quality and prosodic features computed using in-house feature extraction algorithms. These initial CSS stacking classifiers were compared to other multi-classifier systems and the employed standard classifiers built on the same set of speech features. Then, new CSS stacking classifiers were built on RekEmozio using a different set of both acoustic parameters (extended version of the Geneva Minimalistic Acoustic Parameter Set (eGeMAPS)) and standard classifiers and employing the best meta-classifier of the initial experiments. The performance of these two CSS stacking classifiers was evaluated and compared. Finally, the new paradigm was tested on the well-known Berlin Emotional Speech database. We compared the performance of single, standard stacking and CSS stacking systems using the same parametrization of the second phase. All of the classifications were performed at the categorical level, including the six primary emotions plus the neutral one. PMID:26712757

Factors influencing relative speech intelligibility in patients with oral squamous cell carcinoma: a prospective study using automatic, computer-based speech analysis.

PubMed

Stelzle, F; Knipfer, C; Schuster, M; Bocklet, T; Nöth, E; Adler, W; Schempf, L; Vieler, P; Riemann, M; Neukam, F W; Nkenke, E

2013-11-01

Oral squamous cell carcinoma (OSCC) and its treatment impair speech intelligibility by alteration of the vocal tract. The aim of this study was to identify the factors of oral cancer treatment that influence speech intelligibility by means of an automatic, standardized speech-recognition system. The study group comprised 71 patients (mean age 59.89, range 35-82 years) with OSCC ranging from stage T1 to T4 (TNM staging). Tumours were located on the tongue (n=23), lower alveolar crest (n=27), and floor of the mouth (n=21). Reconstruction was conducted through local tissue plasty or microvascular transplants. Adjuvant radiotherapy was performed in 49 patients. Speech intelligibility was evaluated before, and at 3, 6, and 12 months after tumour resection, and compared to that of a healthy control group (n=40). Postoperatively, significant influences on speech intelligibility were tumour localization (P=0.010) and resection volume (P=0.019). Additionally, adjuvant radiotherapy (P=0.049) influenced intelligibility at 3 months after surgery. At 6 months after surgery, influences were resection volume (P=0.028) and adjuvant radiotherapy (P=0.034). The influence of tumour localization (P=0.001) and adjuvant radiotherapy (P=0.022) persisted after 12 months. Tumour localization, resection volume, and radiotherapy are crucial factors for speech intelligibility. Radiotherapy significantly impaired word recognition rate (WR) values with a progression of the impairment for up to 12 months after surgery. Copyright © 2013 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

Speech perception in noise with a harmonic complex excited vocoder.

PubMed

Churchill, Tyler H; Kan, Alan; Goupell, Matthew J; Ihlefeld, Antje; Litovsky, Ruth Y

2014-04-01

A cochlear implant (CI) presents band-pass-filtered acoustic envelope information by modulating current pulse train levels. Similarly, a vocoder presents envelope information by modulating an acoustic carrier. By studying how normal hearing (NH) listeners are able to understand degraded speech signals with a vocoder, the parameters that best simulate electric hearing and factors that might contribute to the NH-CI performance difference may be better understood. A vocoder with harmonic complex carriers (fundamental frequency, f0 = 100 Hz) was used to study the effect of carrier phase dispersion on speech envelopes and intelligibility. The starting phases of the harmonic components were randomly dispersed to varying degrees prior to carrier filtering and modulation. NH listeners were tested on recognition of a closed set of vocoded words in background noise. Two sets of synthesis filters simulated different amounts of current spread in CIs. Results showed that the speech vocoded with carriers whose starting phases were maximally dispersed was the most intelligible. Superior speech understanding may have been a result of the flattening of the dispersed-phase carrier's intrinsic temporal envelopes produced by the large number of interacting components in the high-frequency channels. Cross-correlogram analyses of auditory nerve model simulations confirmed that randomly dispersing the carrier's component starting phases resulted in better neural envelope representation. However, neural metrics extracted from these analyses were not found to accurately predict speech recognition scores for all vocoded speech conditions. It is possible that central speech understanding mechanisms are insensitive to the envelope-fine structure dichotomy exploited by vocoders.

Improving speech perception in noise for children with cochlear implants.

PubMed

Gifford, René H; Olund, Amy P; Dejong, Melissa

2011-10-01

Current cochlear implant recipients are achieving increasingly higher levels of speech recognition; however, the presence of background noise continues to significantly degrade speech understanding for even the best performers. Newer generation Nucleus cochlear implant sound processors can be programmed with SmartSound strategies that have been shown to improve speech understanding in noise for adult cochlear implant recipients. The applicability of these strategies for use in children, however, is not fully understood nor widely accepted. To assess speech perception for pediatric cochlear implant recipients in the presence of a realistic restaurant simulation generated by an eight-loudspeaker (R-SPACE™) array in order to determine whether Nucleus sound processor SmartSound strategies yield improved sentence recognition in noise for children who learn language through the implant. Single subject, repeated measures design. Twenty-two experimental subjects with cochlear implants (mean age 11.1 yr) and 25 control subjects with normal hearing (mean age 9.6 yr) participated in this prospective study. Speech reception thresholds (SRT) in semidiffuse restaurant noise originating from an eight-loudspeaker array were assessed with the experimental subjects' everyday program incorporating Adaptive Dynamic Range Optimization (ADRO) as well as with the addition of Autosensitivity control (ASC). Adaptive SRTs with the Hearing In Noise Test (HINT) sentences were obtained for all 22 experimental subjects, and performance-in percent correct-was assessed in a fixed +6 dB SNR (signal-to-noise ratio) for a six-subject subset. Statistical analysis using a repeated-measures analysis of variance (ANOVA) evaluated the effects of the SmartSound setting on the SRT in noise. The primary findings mirrored those reported previously with adult cochlear implant recipients in that the addition of ASC to ADRO significantly improved speech recognition in noise for pediatric cochlear implant recipients. The mean degree of improvement in the SRT with the addition of ASC to ADRO was 3.5 dB for a mean SRT of 10.9 dB SNR. Thus, despite the fact that these children have acquired auditory/oral speech and language through the use of their cochlear implant(s) equipped with ADRO, the addition of ASC significantly improved their ability to recognize speech in high levels of diffuse background noise. The mean SRT for the control subjects with normal hearing was 0.0 dB SNR. Given that the mean SRT for the experimental group was 10.9 dB SNR, despite the improvements in performance observed with the addition of ASC, cochlear implants still do not completely overcome the speech perception deficit encountered in noisy environments accompanying the diagnosis of severe-to-profound hearing loss. SmartSound strategies currently available in latest generation Nucleus cochlear implant sound processors are able to significantly improve speech understanding in a realistic, semidiffuse noise for pediatric cochlear implant recipients. Despite the reluctance of pediatric audiologists to utilize SmartSound settings for regular use, the results of the current study support the addition of ASC to ADRO for everyday listening environments to improve speech perception in a child's typical everyday program. American Academy of Audiology.

Improving language models for radiology speech recognition.

PubMed

Paulett, John M; Langlotz, Curtis P

2009-02-01

Speech recognition systems have become increasingly popular as a means to produce radiology reports, for reasons both of efficiency and of cost. However, the suboptimal recognition accuracy of these systems can affect the productivity of the radiologists creating the text reports. We analyzed a database of over two million de-identified radiology reports to determine the strongest determinants of word frequency. Our results showed that body site and imaging modality had a similar influence on the frequency of words and of three-word phrases as did the identity of the speaker. These findings suggest that the accuracy of speech recognition systems could be significantly enhanced by further tailoring their language models to body site and imaging modality, which are readily available at the time of report creation.

Across-site patterns of modulation detection: Relation to speech recognitiona)

PubMed Central

Garadat, Soha N.; Zwolan, Teresa A.; Pfingst, Bryan E.

2012-01-01

The aim of this study was to identify across-site patterns of modulation detection thresholds (MDTs) in subjects with cochlear implants and to determine if removal of sites with the poorest MDTs from speech processor programs would result in improved speech recognition. Five hundred millisecond trains of symmetric-biphasic pulses were modulated sinusoidally at 10 Hz and presented at a rate of 900 pps using monopolar stimulation. Subjects were asked to discriminate a modulated pulse train from an unmodulated pulse train for all electrodes in quiet and in the presence of an interleaved unmodulated masker presented on the adjacent site. Across-site patterns of masked MDTs were then used to construct two 10-channel MAPs such that one MAP consisted of sites with the best masked MDTs and the other MAP consisted of sites with the worst masked MDTs. Subjects’ speech recognition skills were compared when they used these two different MAPs. Results showed that MDTs were variable across sites and were elevated in the presence of a masker by various amounts across sites. Better speech recognition was observed when the processor MAP consisted of sites with best masked MDTs, suggesting that temporal modulation sensitivity has important contributions to speech recognition with a cochlear implant. PMID:22559376

Sentence Recognition Prediction for Hearing-impaired Listeners in Stationary and Fluctuation Noise With FADE: Empowering the Attenuation and Distortion Concept by Plomp With a Quantitative Processing Model.

PubMed

Kollmeier, Birger; Schädler, Marc René; Warzybok, Anna; Meyer, Bernd T; Brand, Thomas

2016-09-07

To characterize the individual patient's hearing impairment as obtained with the matrix sentence recognition test, a simulation Framework for Auditory Discrimination Experiments (FADE) is extended here using the Attenuation and Distortion (A+D) approach by Plomp as a blueprint for setting the individual processing parameters. FADE has been shown to predict the outcome of both speech recognition tests and psychoacoustic experiments based on simulations using an automatic speech recognition system requiring only few assumptions. It builds on the closed-set matrix sentence recognition test which is advantageous for testing individual speech recognition in a way comparable across languages. Individual predictions of speech recognition thresholds in stationary and in fluctuating noise were derived using the audiogram and an estimate of the internal level uncertainty for modeling the individual Plomp curves fitted to the data with the Attenuation (A-) and Distortion (D-) parameters of the Plomp approach. The "typical" audiogram shapes from Bisgaard et al with or without a "typical" level uncertainty and the individual data were used for individual predictions. As a result, the individualization of the level uncertainty was found to be more important than the exact shape of the individual audiogram to accurately model the outcome of the German Matrix test in stationary or fluctuating noise for listeners with hearing impairment. The prediction accuracy of the individualized approach also outperforms the (modified) Speech Intelligibility Index approach which is based on the individual threshold data only. © The Author(s) 2016.

Science 101: How Does Speech-Recognition Software Work?

ERIC Educational Resources Information Center

Robertson, Bill

2016-01-01

This column provides background science information for elementary teachers. Many innovations with computer software begin with analysis of how humans do a task. This article takes a look at how humans recognize spoken words and explains the origins of speech-recognition software.

Open fitting: performance verification of receiver in the ear and receiver in the aid.

PubMed

Mondelli, Maria Fernanda Capoani Garcia; Garcia, Tatiana Manfrini; Hashimoto, Fabiana Midori Tokuhara; Rocha, Andressa Vital

2015-01-01

To verify the receiver in the ear and receiver in the aid adaptations by measuring in situ the speech perception and users' level of satisfaction. The study was approved by the research ethics committee (Process: 027/2011). Twenty subjects older than 18 years with audiological diagnosis of mild and moderate bilateral descending sensorineural hearing loss were evaluated. The subjects were divided into two groups, where G1 (group 1) was fitted with open-fit hearing aids with the built-in receiver unit (receiver in the ear) and G2 (group 2) was fitted with open-fit hearing aids with RITE. A probe microphone measurement was performed to check the gain and output provided by the amplification and for assessment of speech perception with Hearing in Noise Test with and without hearing aids. After a period of six weeks of use without interruption, the subjects returned for follow-up and answered the Satisfaction with Amplification in Daily Life questionnaire, and were again subjected to Hearing in Noise Test. Both groups presented better test results for speech recognition in the presence of noise. Groups 1 and 2 were satisfied with the use of hearing aids and improved speech recognition in silent and noisy situations with hearing aids. Copyright © 2014 Associação Brasileira de Otorrinolaringologia e Cirurgia Cérvico-Facial. Published by Elsevier Editora Ltda. All rights reserved.

Noise reduction technologies implemented in head-worn preprocessors for improving cochlear implant performance in reverberant noise fields.

PubMed

Chung, King; Nelson, Lance; Teske, Melissa

2012-09-01

The purpose of this study was to investigate whether a multichannel adaptive directional microphone and a modulation-based noise reduction algorithm could enhance cochlear implant performance in reverberant noise fields. A hearing aid was modified to output electrical signals (ePreprocessor) and a cochlear implant speech processor was modified to receive electrical signals (eProcessor). The ePreprocessor was programmed to flat frequency response and linear amplification. Cochlear implant listeners wore the ePreprocessor-eProcessor system in three reverberant noise fields: 1) one noise source with variable locations; 2) three noise sources with variable locations; and 3) eight evenly spaced noise sources from 0° to 360°. Listeners' speech recognition scores were tested when the ePreprocessor was programmed to omnidirectional microphone (OMNI), omnidirectional microphone plus noise reduction algorithm (OMNI + NR), and adaptive directional microphone plus noise reduction algorithm (ADM + NR). They were also tested with their own cochlear implant speech processor (CI_OMNI) in the three noise fields. Additionally, listeners rated overall sound quality preferences on recordings made in the noise fields. Results indicated that ADM+NR produced the highest speech recognition scores and the most preferable rating in all noise fields. Factors requiring attention in the hearing aid-cochlear implant integration process are discussed. Copyright © 2012 Elsevier B.V. All rights reserved.

Perception and performance in flight simulators: The contribution of vestibular, visual, and auditory information

NASA Technical Reports Server (NTRS)

1979-01-01

The pilot's perception and performance in flight simulators is examined. The areas investigated include: vestibular stimulation, flight management and man cockpit information interfacing, and visual perception in flight simulation. The effects of higher levels of rotary acceleration on response time to constant acceleration, tracking performance, and thresholds for angular acceleration are examined. Areas of flight management examined are cockpit display of traffic information, work load, synthetic speech call outs during the landing phase of flight, perceptual factors in the use of a microwave landing system, automatic speech recognition, automation of aircraft operation, and total simulation of flight training.

Watch what you say, your computer might be listening: A review of automated speech recognition

NASA Technical Reports Server (NTRS)

Degennaro, Stephen V.

1991-01-01

Spoken language is the most convenient and natural means by which people interact with each other and is, therefore, a promising candidate for human-machine interactions. Speech also offers an additional channel for hands-busy applications, complementing the use of motor output channels for control. Current speech recognition systems vary considerably across a number of important characteristics, including vocabulary size, speaking mode, training requirements for new speakers, robustness to acoustic environments, and accuracy. Algorithmically, these systems range from rule-based techniques through more probabilistic or self-learning approaches such as hidden Markov modeling and neural networks. This tutorial begins with a brief summary of the relevant features of current speech recognition systems and the strengths and weaknesses of the various algorithmic approaches.

Speech endpoint detection with non-language speech sounds for generic speech processing applications

NASA Astrophysics Data System (ADS)

McClain, Matthew; Romanowski, Brian

2009-05-01

Non-language speech sounds (NLSS) are sounds produced by humans that do not carry linguistic information. Examples of these sounds are coughs, clicks, breaths, and filled pauses such as "uh" and "um" in English. NLSS are prominent in conversational speech, but can be a significant source of errors in speech processing applications. Traditionally, these sounds are ignored by speech endpoint detection algorithms, where speech regions are identified in the audio signal prior to processing. The ability to filter NLSS as a pre-processing step can significantly enhance the performance of many speech processing applications, such as speaker identification, language identification, and automatic speech recognition. In order to be used in all such applications, NLSS detection must be performed without the use of language models that provide knowledge of the phonology and lexical structure of speech. This is especially relevant to situations where the languages used in the audio are not known apriori. We present the results of preliminary experiments using data from American and British English speakers, in which segments of audio are classified as language speech sounds (LSS) or NLSS using a set of acoustic features designed for language-agnostic NLSS detection and a hidden-Markov model (HMM) to model speech generation. The results of these experiments indicate that the features and model used are capable of detection certain types of NLSS, such as breaths and clicks, while detection of other types of NLSS such as filled pauses will require future research.

Investigating speech perception in children with dyslexia: is there evidence of a consistent deficit in individuals?

PubMed Central

Messaoud-Galusi, Souhila; Hazan, Valerie; Rosen, Stuart

2012-01-01

Purpose The claim that speech perception abilities are impaired in dyslexia was investigated in a group of 62 dyslexic children and 51 average readers matched in age. Method To test whether there was robust evidence of speech perception deficits in children with dyslexia, speech perception in noise and quiet was measured using eight different tasks involving the identification and discrimination of a complex and highly natural synthetic ‘pea’-‘bee’ contrast (copy synthesised from natural models) and the perception of naturally-produced words. Results Children with dyslexia, on average, performed more poorly than average readers in the synthetic syllables identification task in quiet and in across-category discrimination (but not when tested using an adaptive procedure). They did not differ from average readers on two tasks of word recognition in noise or identification of synthetic syllables in noise. For all tasks, a majority of individual children with dyslexia performed within norms. Finally, speech perception generally did not correlate with pseudo-word reading or phonological processing, the core skills related to dyslexia. Conclusions On the tasks and speech stimuli we used, most children with dyslexia do not appear to show a consistent deficit in speech perception. PMID:21930615

Analytic study of the Tadoma method: background and preliminary results.

PubMed

Norton, S J; Schultz, M C; Reed, C M; Braida, L D; Durlach, N I; Rabinowitz, W M; Chomsky, C

1977-09-01

Certain deaf-blind persons have been taught, through the Tadoma method of speechreading, to use vibrotactile cues from the face and neck to understand speech. This paper reports the results of preliminary tests of the speechreading ability of one adult Tadoma user. The tests were of four major types: (1) discrimination of speech stimuli; (2) recognition of words in isolation and in sentences; (3) interpretation of prosodic and syntactic features in sentences; and (4) comprehension of written (Braille) and oral speech. Words in highly contextual environments were much better perceived than were words in low-context environments. Many of the word errors involved phonemic substitutions which shared articulatory features with the target phonemes, with a higher error rate for vowels than consonants. Relative to performance on word-recognition tests, performance on some of the discrimination tests was worse than expected. Perception of sentences appeared to be mildly sensitive to rate of talking and to speaker differences. Results of the tests on perception of prosodic and syntactic features, while inconclusive, indicate that many of the features tested were not used in interpreting sentences. On an English comprehension test, a higher score was obtained for items administered in Braille than through oral presentation.

Lexico-semantic and acoustic-phonetic processes in the perception of noise-vocoded speech: implications for cochlear implantation

PubMed Central

McGettigan, Carolyn; Rosen, Stuart; Scott, Sophie K.

2014-01-01

Noise-vocoding is a transformation which, when applied to speech, severely reduces spectral resolution and eliminates periodicity, yielding a stimulus that sounds “like a harsh whisper” (Scott et al., 2000, p. 2401). This process simulates a cochlear implant, where the activity of many thousand hair cells in the inner ear is replaced by direct stimulation of the auditory nerve by a small number of tonotopically-arranged electrodes. Although a cochlear implant offers a powerful means of restoring some degree of hearing to profoundly deaf individuals, the outcomes for spoken communication are highly variable (Moore and Shannon, 2009). Some variability may arise from differences in peripheral representation (e.g., the degree of residual nerve survival) but some may reflect differences in higher-order linguistic processing. In order to explore this possibility, we used noise-vocoding to explore speech recognition and perceptual learning in normal-hearing listeners tested across several levels of the linguistic hierarchy: segments (consonants and vowels), single words, and sentences. Listeners improved significantly on all tasks across two test sessions. In the first session, individual differences analyses revealed two independently varying sources of variability: one lexico-semantic in nature and implicating the recognition of words and sentences, and the other an acoustic-phonetic factor associated with words and segments. However, consequent to learning, by the second session there was a more uniform covariance pattern concerning all stimulus types. A further analysis of phonetic feature recognition allowed greater insight into learning-related changes in perception and showed that, surprisingly, participants did not make full use of cues that were preserved in the stimuli (e.g., vowel duration). We discuss these findings in relation cochlear implantation, and suggest auditory training strategies to maximize speech recognition performance in the absence of typical cues. PMID:24616669

Sperry Univac speech communications technology

NASA Technical Reports Server (NTRS)

Medress, Mark F.

1977-01-01

Technology and systems for effective verbal communication with computers were developed. A continuous speech recognition system for verbal input, a word spotting system to locate key words in conversational speech, prosodic tools to aid speech analysis, and a prerecorded voice response system for speech output are described.

Assistive Technology and Adults with Learning Disabilities: A Blueprint for Exploration and Advancement.

ERIC Educational Resources Information Center

Raskind, Marshall

1993-01-01

This article describes assistive technologies for persons with learning disabilities, including word processing, spell checking, proofreading programs, outlining/"brainstorming" programs, abbreviation expanders, speech recognition, speech synthesis/screen review, optical character recognition systems, personal data managers, free-form databases,…

Speech Recognition for A Digital Video Library.

ERIC Educational Resources Information Center

Witbrock, Michael J.; Hauptmann, Alexander G.

1998-01-01

Production of the meta-data supporting the Informedia Digital Video Library interface is automated using techniques derived from artificial intelligence research. Speech recognition and natural-language processing, information retrieval, and image analysis are applied to produce an interface that helps users locate information and navigate more…

Extrinsic Cognitive Load Impairs Spoken Word Recognition in High- and Low-Predictability Sentences.

PubMed

Hunter, Cynthia R; Pisoni, David B

Listening effort (LE) induced by speech degradation reduces performance on concurrent cognitive tasks. However, a converse effect of extrinsic cognitive load on recognition of spoken words in sentences has not been shown. The aims of the present study were to (a) examine the impact of extrinsic cognitive load on spoken word recognition in a sentence recognition task and (b) determine whether cognitive load and/or LE needed to understand spectrally degraded speech would differentially affect word recognition in high- and low-predictability sentences. Downstream effects of speech degradation and sentence predictability on the cognitive load task were also examined. One hundred twenty young adults identified sentence-final spoken words in high- and low-predictability Speech Perception in Noise sentences. Cognitive load consisted of a preload of short (low-load) or long (high-load) sequences of digits, presented visually before each spoken sentence and reported either before or after identification of the sentence-final word. LE was varied by spectrally degrading sentences with four-, six-, or eight-channel noise vocoding. Level of spectral degradation and order of report (digits first or words first) were between-participants variables. Effects of cognitive load, sentence predictability, and speech degradation on accuracy of sentence-final word identification as well as recall of preload digit sequences were examined. In addition to anticipated main effects of sentence predictability and spectral degradation on word recognition, we found an effect of cognitive load, such that words were identified more accurately under low load than high load. However, load differentially affected word identification in high- and low-predictability sentences depending on the level of sentence degradation. Under severe spectral degradation (four-channel vocoding), the effect of cognitive load on word identification was present for high-predictability sentences but not for low-predictability sentences. Under mild spectral degradation (eight-channel vocoding), the effect of load was present for low-predictability sentences but not for high-predictability sentences. There were also reliable downstream effects of speech degradation and sentence predictability on recall of the preload digit sequences. Long digit sequences were more easily recalled following spoken sentences that were less spectrally degraded. When digits were reported after identification of sentence-final words, short digit sequences were recalled more accurately when the spoken sentences were predictable. Extrinsic cognitive load can impair recognition of spectrally degraded spoken words in a sentence recognition task. Cognitive load affected word identification in both high- and low-predictability sentences, suggesting that load may impact both context use and lower-level perceptual processes. Consistent with prior work, LE also had downstream effects on memory for visual digit sequences. Results support the proposal that extrinsic cognitive load and LE induced by signal degradation both draw on a central, limited pool of cognitive resources that is used to recognize spoken words in sentences under adverse listening conditions.

Speech as a pilot input medium

NASA Technical Reports Server (NTRS)

Plummer, R. P.; Coler, C. R.

1977-01-01

The speech recognition system under development is a trainable pattern classifier based on a maximum-likelihood technique. An adjustable uncertainty threshold allows the rejection of borderline cases for which the probability of misclassification is high. The syntax of the command language spoken may be used as an aid to recognition, and the system adapts to changes in pronunciation if feedback from the user is available. Words must be separated by .25 second gaps. The system runs in real time on a mini-computer (PDP 11/10) and was tested on 120,000 speech samples from 10- and 100-word vocabularies. The results of these tests were 99.9% correct recognition for a vocabulary consisting of the ten digits, and 99.6% recognition for a 100-word vocabulary of flight commands, with a 5% rejection rate in each case. With no rejection, the recognition accuracies for the same vocabularies were 99.5% and 98.6% respectively.

Listeners Experience Linguistic Masking Release in Noise-Vocoded Speech-in-Speech Recognition

ERIC Educational Resources Information Center

Viswanathan, Navin; Kokkinakis, Kostas; Williams, Brittany T.

2018-01-01

Purpose: The purpose of this study was to evaluate whether listeners with normal hearing perceiving noise-vocoded speech-in-speech demonstrate better intelligibility of target speech when the background speech was mismatched in language (linguistic release from masking [LRM]) and/or location (spatial release from masking [SRM]) relative to the…

Detection of target phonemes in spontaneous and read speech.

PubMed

Mehta, G; Cutler, A

1988-01-01

Although spontaneous speech occurs more frequently in most listeners' experience than read speech, laboratory studies of human speech recognition typically use carefully controlled materials read from a script. The phonological and prosodic characteristics of spontaneous and read speech differ considerably, however, which suggests that laboratory results may not generalise to the recognition of spontaneous speech. In the present study listeners were presented with both spontaneous and read speech materials, and their response time to detect word-initial target phonemes was measured. Responses were, overall, equally fast in each speech mode. However, analysis of effects previously reported in phoneme detection studies revealed significant differences between speech modes. In read speech but not in spontaneous speech, later targets were detected more rapidly than targets preceded by short words. In contrast, in spontaneous speech but not in read speech, targets were detected more rapidly in accented than in unaccented words and in strong than in weak syllables. An explanation for this pattern is offered in terms of characteristic prosodic differences between spontaneous and read speech. The results support claims from previous work that listeners pay great attention to prosodic information in the process of recognising speech.

Acoustic landmarks contain more information about the phone string than other frames for automatic speech recognition with deep neural network acoustic model

NASA Astrophysics Data System (ADS)

He, Di; Lim, Boon Pang; Yang, Xuesong; Hasegawa-Johnson, Mark; Chen, Deming

2018-06-01

Most mainstream Automatic Speech Recognition (ASR) systems consider all feature frames equally important. However, acoustic landmark theory is based on a contradictory idea, that some frames are more important than others. Acoustic landmark theory exploits quantal non-linearities in the articulatory-acoustic and acoustic-perceptual relations to define landmark times at which the speech spectrum abruptly changes or reaches an extremum; frames overlapping landmarks have been demonstrated to be sufficient for speech perception. In this work, we conduct experiments on the TIMIT corpus, with both GMM and DNN based ASR systems and find that frames containing landmarks are more informative for ASR than others. We find that altering the level of emphasis on landmarks by re-weighting acoustic likelihood tends to reduce the phone error rate (PER). Furthermore, by leveraging the landmark as a heuristic, one of our hybrid DNN frame dropping strategies maintained a PER within 0.44% of optimal when scoring less than half (45.8% to be precise) of the frames. This hybrid strategy out-performs other non-heuristic-based methods and demonstrate the potential of landmarks for reducing computation.

LANDMARK-BASED SPEECH RECOGNITION: REPORT OF THE 2004 JOHNS HOPKINS SUMMER WORKSHOP.

PubMed

Hasegawa-Johnson, Mark; Baker, James; Borys, Sarah; Chen, Ken; Coogan, Emily; Greenberg, Steven; Juneja, Amit; Kirchhoff, Katrin; Livescu, Karen; Mohan, Srividya; Muller, Jennifer; Sonmez, Kemal; Wang, Tianyu

2005-01-01

Three research prototype speech recognition systems are described, all of which use recently developed methods from artificial intelligence (specifically support vector machines, dynamic Bayesian networks, and maximum entropy classification) in order to implement, in the form of an automatic speech recognizer, current theories of human speech perception and phonology (specifically landmark-based speech perception, nonlinear phonology, and articulatory phonology). All three systems begin with a high-dimensional multiframe acoustic-to-distinctive feature transformation, implemented using support vector machines trained to detect and classify acoustic phonetic landmarks. Distinctive feature probabilities estimated by the support vector machines are then integrated using one of three pronunciation models: a dynamic programming algorithm that assumes canonical pronunciation of each word, a dynamic Bayesian network implementation of articulatory phonology, or a discriminative pronunciation model trained using the methods of maximum entropy classification. Log probability scores computed by these models are then combined, using log-linear combination, with other word scores available in the lattice output of a first-pass recognizer, and the resulting combination score is used to compute a second-pass speech recognition output.

An Analysis of Individual Differences in Recognizing Monosyllabic Words Under the Speech Intelligibility Index Framework

PubMed Central

Shen, Yi; Kern, Allison B.

2018-01-01

Individual differences in the recognition of monosyllabic words, either in isolation (NU6 test) or in sentence context (SPIN test), were investigated under the theoretical framework of the speech intelligibility index (SII). An adaptive psychophysical procedure, namely the quick-band-importance-function procedure, was developed to enable the fitting of the SII model to individual listeners. Using this procedure, the band importance function (i.e., the relative weights of speech information across the spectrum) and the link function relating the SII to recognition scores can be simultaneously estimated while requiring only 200 to 300 trials of testing. Octave-frequency band importance functions and link functions were estimated separately for NU6 and SPIN materials from 30 normal-hearing listeners who were naïve to speech recognition experiments. For each type of speech material, considerable individual differences in the spectral weights were observed in some but not all frequency regions. At frequencies where the greatest intersubject variability was found, the spectral weights were correlated between the two speech materials, suggesting that the variability in spectral weights reflected listener-originated factors. PMID:29532711

Application of Business Process Management to drive the deployment of a speech recognition system in a healthcare organization.

PubMed

González Sánchez, María José; Framiñán Torres, José Manuel; Parra Calderón, Carlos Luis; Del Río Ortega, Juan Antonio; Vigil Martín, Eduardo; Nieto Cervera, Jaime

2008-01-01

We present a methodology based on Business Process Management to guide the development of a speech recognition system in a hospital in Spain. The methodology eases the deployment of the system by 1) involving the clinical staff in the process, 2) providing the IT professionals with a description of the process and its requirements, 3) assessing advantages and disadvantages of the speech recognition system, as well as its impact in the organisation, and 4) help reorganising the healthcare process before implementing the new technology in order to identify how it can better contribute to the overall objective of the organisation.

Psychometric Functions for Shortened Administrations of a Speech Recognition Approach Using Tri-Word Presentations and Phonemic Scoring

ERIC Educational Resources Information Center

Gelfand, Stanley A.; Gelfand, Jessica T.

2012-01-01

Method: Complete psychometric functions for phoneme and word recognition scores at 8 signal-to-noise ratios from -15 dB to 20 dB were generated for the first 10, 20, and 25, as well as all 50, three-word presentations of the Tri-Word or Computer Assisted Speech Recognition Assessment (CASRA) Test (Gelfand, 1998) based on the results of 12…

Adaptive method of recognition of signals for one and two-frequency signal system in the telephony on the background of speech

NASA Astrophysics Data System (ADS)

Kuznetsov, Michael V.

2006-05-01

For reliable teamwork of various systems of automatic telecommunication including transferring systems of optical communication networks it is necessary authentic recognition of signals for one- or two-frequency service signal system. The analysis of time parameters of an accepted signal allows increasing reliability of detection and recognition of the service signal system on a background of speech.

Automatic measurement and representation of prosodic features

NASA Astrophysics Data System (ADS)

Ying, Goangshiuan Shawn

Effective measurement and representation of prosodic features of the acoustic signal for use in automatic speech recognition and understanding systems is the goal of this work. Prosodic features-stress, duration, and intonation-are variations of the acoustic signal whose domains are beyond the boundaries of each individual phonetic segment. Listeners perceive prosodic features through a complex combination of acoustic correlates such as intensity, duration, and fundamental frequency (F0). We have developed new tools to measure F0 and intensity features. We apply a probabilistic global error correction routine to an Average Magnitude Difference Function (AMDF) pitch detector. A new short-term frequency-domain Teager energy algorithm is used to measure the energy of a speech signal. We have conducted a series of experiments performing lexical stress detection on words in continuous English speech from two speech corpora. We have experimented with two different approaches, a segment-based approach and a rhythm unit-based approach, in lexical stress detection. The first approach uses pattern recognition with energy- and duration-based measurements as features to build Bayesian classifiers to detect the stress level of a vowel segment. In the second approach we define rhythm unit and use only the F0-based measurement and a scoring system to determine the stressed segment in the rhythm unit. A duration-based segmentation routine was developed to break polysyllabic words into rhythm units. The long-term goal of this work is to develop a system that can effectively detect the stress pattern for each word in continuous speech utterances. Stress information will be integrated as a constraint for pruning the word hypotheses in a word recognition system based on hidden Markov models.

[Improvement in Phoneme Discrimination in Noise in Normal Hearing Adults].

PubMed

Schumann, A; Garea Garcia, L; Hoppe, U

2017-02-01

Objective: The study's aim was to examine the possibility to train phoneme-discrimination in noise with normal hearing adults, and its effectivity on speech recognition in noise. A specific computerised training program was used, consisting of special nonsense-syllables with background noise, to train participants' discrimination ability. Material and Methods: 46 normal hearing subjects took part in this study, 28 as training group participants, 18 as control group participants. Only the training group subjects were asked to train over a period of 3 weeks, twice a week for an hour with a computer-based training program. Speech recognition in noise were measured pre- to posttraining for the training group subjects with the Freiburger Einsilber Test. The control group subjects obtained test and restest measures within a 2-3 week break. For the training group follow-up speech recognition was measured 2-3 months after the end of the training. Results: The majority of training group subjects improved their phoneme discrimination significantly. Besides, their speech recognition in noise improved significantly during the training compared to the control group, and remained stable for a period of time. Conclusions: Phonem-Discrimination in noise can be trained by normal hearing adults. The improvements have got a positiv effect on speech recognition in noise, also for a longer period of time. © Georg Thieme Verlag KG Stuttgart · New York.

Pattern learning with deep neural networks in EMG-based speech recognition.

PubMed

Wand, Michael; Schultz, Tanja

2014-01-01

We report on classification of phones and phonetic features from facial electromyographic (EMG) data, within the context of our EMG-based Silent Speech interface. In this paper we show that a Deep Neural Network can be used to perform this classification task, yielding a significant improvement over conventional Gaussian Mixture models. Our central contribution is the visualization of patterns which are learned by the neural network. With increasing network depth, these patterns represent more and more intricate electromyographic activity.