Automatic detection of Parkinson's disease in running speech spoken in three different languages.
Orozco-Arroyave, J R; Hönig, F; Arias-Londoño, J D; Vargas-Bonilla, J F; Daqrouq, K; Skodda, S; Rusz, J; Nöth, E
2016-01-01
The aim of this study is the analysis of continuous speech signals of people with Parkinson's disease (PD) considering recordings in different languages (Spanish, German, and Czech). A method for the characterization of the speech signals, based on the automatic segmentation of utterances into voiced and unvoiced frames, is addressed here. The energy content of the unvoiced sounds is modeled using 12 Mel-frequency cepstral coefficients and 25 bands scaled according to the Bark scale. Four speech tasks comprising isolated words, rapid repetition of the syllables /pa/-/ta/-/ka/, sentences, and read texts are evaluated. The method proves to be more accurate than classical approaches in the automatic classification of speech of people with PD and healthy controls. The accuracies range from 85% to 99% depending on the language and the speech task. Cross-language experiments are also performed confirming the robustness and generalization capability of the method, with accuracies ranging from 60% to 99%. This work comprises a step forward for the development of computer aided tools for the automatic assessment of dysarthric speech signals in multiple languages.
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.
Accurate visible speech synthesis based on concatenating variable length motion capture data.
Ma, Jiyong; Cole, Ron; Pellom, Bryan; Ward, Wayne; Wise, Barbara
2006-01-01
We present a novel approach to synthesizing accurate visible speech based on searching and concatenating optimal variable-length units in a large corpus of motion capture data. Based on a set of visual prototypes selected on a source face and a corresponding set designated for a target face, we propose a machine learning technique to automatically map the facial motions observed on the source face to the target face. In order to model the long distance coarticulation effects in visible speech, a large-scale corpus that covers the most common syllables in English was collected, annotated and analyzed. For any input text, a search algorithm to locate the optimal sequences of concatenated units for synthesis is desrcribed. A new algorithm to adapt lip motions from a generic 3D face model to a specific 3D face model is also proposed. A complete, end-to-end visible speech animation system is implemented based on the approach. This system is currently used in more than 60 kindergarten through third grade classrooms to teach students to read using a lifelike conversational animated agent. To evaluate the quality of the visible speech produced by the animation system, both subjective evaluation and objective evaluation are conducted. The evaluation results show that the proposed approach is accurate and powerful for visible speech synthesis.
Automatic Speech Recognition from Neural Signals: A Focused Review.
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.
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.
Visual speech influences speech perception immediately but not automatically.
Mitterer, Holger; Reinisch, Eva
2017-02-01
Two experiments examined the time course of the use of auditory and visual speech cues to spoken word recognition using an eye-tracking paradigm. Results of the first experiment showed that the use of visual speech cues from lipreading is reduced if concurrently presented pictures require a division of attentional resources. This reduction was evident even when listeners' eye gaze was on the speaker rather than the (static) pictures. Experiment 2 used a deictic hand gesture to foster attention to the speaker. At the same time, the visual processing load was reduced by keeping the visual display constant over a fixed number of successive trials. Under these conditions, the visual speech cues from lipreading were used. Moreover, the eye-tracking data indicated that visual information was used immediately and even earlier than auditory information. In combination, these data indicate that visual speech cues are not used automatically, but if they are used, they are used immediately.
ERIC Educational Resources Information Center
Young, Victoria; Mihailidis, Alex
2010-01-01
Despite their growing presence in home computer applications and various telephony services, commercial automatic speech recognition technologies are still not easily employed by everyone; especially individuals with speech disorders. In addition, relatively little research has been conducted on automatic speech recognition performance with older…
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
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
Zekveld, Adriana A; Kramer, Sophia E; Kessens, Judith M; Vlaming, Marcel S M G; Houtgast, Tammo
2009-04-01
The aim of the current study was to examine whether partly incorrect subtitles that are automatically generated by an Automatic Speech Recognition (ASR) system, improve speech comprehension by listeners with hearing impairment. In an earlier study (Zekveld et al. 2008), we showed that speech comprehension in noise by young listeners with normal hearing improves when presenting partly incorrect, automatically generated subtitles. The current study focused on the effects of age, hearing loss, visual working memory capacity, and linguistic skills on the benefit obtained from automatically generated subtitles during listening to speech in noise. In order to investigate the effects of age and hearing loss, three groups of participants were included: 22 young persons with normal hearing (YNH, mean age = 21 years), 22 middle-aged adults with normal hearing (MA-NH, mean age = 55 years) and 30 middle-aged adults with hearing impairment (MA-HI, mean age = 57 years). The benefit from automatic subtitling was measured by Speech Reception Threshold (SRT) tests (Plomp & Mimpen, 1979). Both unimodal auditory and bimodal audiovisual SRT tests were performed. In the audiovisual tests, the subtitles were presented simultaneously with the speech, whereas in the auditory test, only speech was presented. The difference between the auditory and audiovisual SRT was defined as the audiovisual benefit. Participants additionally rated the listening effort. We examined the influences of ASR accuracy level and text delay on the audiovisual benefit and the listening effort using a repeated measures General Linear Model analysis. In a correlation analysis, we evaluated the relationships between age, auditory SRT, visual working memory capacity and the audiovisual benefit and listening effort. The automatically generated subtitles improved speech comprehension in noise for all ASR accuracies and delays covered by the current study. Higher ASR accuracy levels resulted in more benefit obtained
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.
Automatic Method of Pause Measurement for Normal and Dysarthric Speech
ERIC Educational Resources Information Center
Rosen, Kristin; Murdoch, Bruce; Folker, Joanne; Vogel, Adam; Cahill, Louise; Delatycki, Martin; Corben, Louise
2010-01-01
This study proposes an automatic method for the detection of pauses and identification of pause types in conversational speech for the purpose of measuring the effects of Friedreich's Ataxia (FRDA) on speech. Speech samples of [approximately] 3 minutes were recorded from 13 speakers with FRDA and 18 healthy controls. Pauses were measured from the…
Integrating hidden Markov model and PRAAT: a toolbox for robust automatic speech transcription
NASA Astrophysics Data System (ADS)
Kabir, A.; Barker, J.; Giurgiu, M.
2010-09-01
An automatic time-aligned phone transcription toolbox of English speech corpora has been developed. Especially the toolbox would be very useful to generate robust automatic transcription and able to produce phone level transcription using speaker independent models as well as speaker dependent models without manual intervention. The system is based on standard Hidden Markov Models (HMM) approach and it was successfully experimented over a large audiovisual speech corpus namely GRID corpus. One of the most powerful features of the toolbox is the increased flexibility in speech processing where the speech community would be able to import the automatic transcription generated by HMM Toolkit (HTK) into a popular transcription software, PRAAT, and vice-versa. The toolbox has been evaluated through statistical analysis on GRID data which shows that automatic transcription deviates by an average of 20 ms with respect to manual transcription.
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.
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…
Automatic speech recognition in air traffic control
NASA Technical Reports Server (NTRS)
Karlsson, Joakim
1990-01-01
Automatic Speech Recognition (ASR) technology and its application to the Air Traffic Control system are described. The advantages of applying ASR to Air Traffic Control, as well as criteria for choosing a suitable ASR system are presented. Results from previous research and directions for future work at the Flight Transportation Laboratory are outlined.
Assessing Children's Home Language Environments Using Automatic Speech Recognition Technology
ERIC Educational Resources Information Center
Greenwood, Charles R.; Thiemann-Bourque, Kathy; Walker, Dale; Buzhardt, Jay; Gilkerson, Jill
2011-01-01
The purpose of this research was to replicate and extend some of the findings of Hart and Risley using automatic speech processing instead of human transcription of language samples. The long-term goal of this work is to make the current approach to speech processing possible by researchers and clinicians working on a daily basis with families and…
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.
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.
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.
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…
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,…
Automatic evaluation of hypernasality based on a cleft palate speech database.
He, Ling; Zhang, Jing; Liu, Qi; Yin, Heng; Lech, Margaret; Huang, Yunzhi
2015-05-01
The hypernasality is one of the most typical characteristics of cleft palate (CP) speech. The evaluation outcome of hypernasality grading decides the necessity of follow-up surgery. Currently, the evaluation of CP speech is carried out by experienced speech therapists. However, the result strongly depends on their clinical experience and subjective judgment. This work aims to propose an automatic evaluation system for hypernasality grading in CP speech. The database tested in this work is collected by the Hospital of Stomatology, Sichuan University, which has the largest number of CP patients in China. Based on the production process of hypernasality, source sound pulse and vocal tract filter features are presented. These features include pitch, the first and second energy amplified frequency bands, cepstrum based features, MFCC, short-time energy in the sub-bands features. These features combined with KNN classier are applied to automatically classify four grades of hypernasality: normal, mild, moderate and severe. The experiment results show that the proposed system achieves a good performance. The classification rates for four hypernasality grades reach up to 80.4%. The sensitivity of proposed features to the gender is also discussed.
Vitikainen, Anne-Mari; Mäkelä, Elina; Lioumis, Pantelis; Jousmäki, Veikko; Mäkelä, Jyrki P
2015-09-30
The use of navigated repetitive transcranial magnetic stimulation (rTMS) in mapping of speech-related brain areas has recently shown to be useful in preoperative workflow of epilepsy and tumor patients. However, substantial inter- and intraobserver variability and non-optimal replicability of the rTMS results have been reported, and a need for additional development of the methodology is recognized. In TMS motor cortex mappings the evoked responses can be quantitatively monitored by electromyographic recordings; however, no such easily available setup exists for speech mappings. We present an accelerometer-based setup for detection of vocalization-related larynx vibrations combined with an automatic routine for voice onset detection for rTMS speech mapping applying naming. The results produced by the automatic routine were compared with the manually reviewed video-recordings. The new method was applied in the routine navigated rTMS speech mapping for 12 consecutive patients during preoperative workup for epilepsy or tumor surgery. The automatic routine correctly detected 96% of the voice onsets, resulting in 96% sensitivity and 71% specificity. Majority (63%) of the misdetections were related to visible throat movements, extra voices before the response, or delayed naming of the previous stimuli. The no-response errors were correctly detected in 88% of events. The proposed setup for automatic detection of voice onsets provides quantitative additional data for analysis of the rTMS-induced speech response modifications. The objectively defined speech response latencies increase the repeatability, reliability and stratification of the rTMS results. Copyright © 2015 Elsevier B.V. All rights reserved.
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…
Automatic speech recognition using a predictive echo state network classifier.
Skowronski, Mark D; Harris, John G
2007-04-01
We have combined an echo state network (ESN) with a competitive state machine framework to create a classification engine called the predictive ESN classifier. We derive the expressions for training the predictive ESN classifier and show that the model was significantly more noise robust compared to a hidden Markov model in noisy speech classification experiments by 8+/-1 dB signal-to-noise ratio. The simple training algorithm and noise robustness of the predictive ESN classifier make it an attractive classification engine for automatic speech recognition.
Automatic Speech Acquisition and Recognition for Spacesuit Audio Systems
NASA Technical Reports Server (NTRS)
Ye, Sherry
2015-01-01
NASA has a widely recognized but unmet need for novel human-machine interface technologies that can facilitate communication during astronaut extravehicular activities (EVAs), when loud noises and strong reverberations inside spacesuits make communication challenging. WeVoice, Inc., has developed a multichannel signal-processing method for speech acquisition in noisy and reverberant environments that enables automatic speech recognition (ASR) technology inside spacesuits. The technology reduces noise by exploiting differences between the statistical nature of signals (i.e., speech) and noise that exists in the spatial and temporal domains. As a result, ASR accuracy can be improved to the level at which crewmembers will find the speech interface useful. System components and features include beam forming/multichannel noise reduction, single-channel noise reduction, speech feature extraction, feature transformation and normalization, feature compression, and ASR decoding. Arithmetic complexity models were developed and will help designers of real-time ASR systems select proper tasks when confronted with constraints in computational resources. In Phase I of the project, WeVoice validated the technology. The company further refined the technology in Phase II and developed a prototype for testing and use by suited astronauts.
Automatic intelligibility classification of sentence-level pathological speech
Kim, Jangwon; Kumar, Naveen; Tsiartas, Andreas; Li, Ming; Narayanan, Shrikanth S.
2014-01-01
Pathological speech usually refers to the condition of speech distortion resulting from atypicalities in voice and/or in the articulatory mechanisms owing to disease, illness or other physical or biological insult to the production system. Although automatic evaluation of speech intelligibility and quality could come in handy in these scenarios to assist experts in diagnosis and treatment design, the many sources and types of variability often make it a very challenging computational processing problem. In this work we propose novel sentence-level features to capture abnormal variation in the prosodic, voice quality and pronunciation aspects in pathological speech. In addition, we propose a post-classification posterior smoothing scheme which refines the posterior of a test sample based on the posteriors of other test samples. Finally, we perform feature-level fusions and subsystem decision fusion for arriving at a final intelligibility decision. The performances are tested on two pathological speech datasets, the NKI CCRT Speech Corpus (advanced head and neck cancer) and the TORGO database (cerebral palsy or amyotrophic lateral sclerosis), by evaluating classification accuracy without overlapping subjects’ data among training and test partitions. Results show that the feature sets of each of the voice quality subsystem, prosodic subsystem, and pronunciation subsystem, offer significant discriminating power for binary intelligibility classification. We observe that the proposed posterior smoothing in the acoustic space can further reduce classification errors. The smoothed posterior score fusion of subsystems shows the best classification performance (73.5% for unweighted, and 72.8% for weighted, average recalls of the binary classes). PMID:25414544
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…
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…
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.
NASA Astrophysics Data System (ADS)
Fernández Pozo, Rubén; Blanco Murillo, Jose Luis; Hernández Gómez, Luis; López Gonzalo, Eduardo; Alcázar Ramírez, José; Toledano, Doroteo T.
2009-12-01
This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.
Lancioni, Giulio E; Singh, Nirbhay N; O'Reilly, Mark F; Green, Vanessa A; Alberti, Gloria; Boccasini, Adele; Smaldone, Angela; Oliva, Doretta; Bosco, Andrea
2014-08-01
Assessing automatic feedback technologies to promote safe travel and speech loudness control in two men with multiple disabilities, respectively. The men were involved in two single-case studies. In Study I, the technology involved a microprocessor, two photocells, and a verbal feedback device. The man received verbal alerting/feedback when the photocells spotted an obstacle in front of him. In Study II, the technology involved a sound-detecting unit connected to a throat and an airborne microphone, and to a vibration device. Vibration occurred when the man's speech loudness exceeded a preset level. The man included in Study I succeeded in using the automatic feedback in substitution of caregivers' alerting/feedback for safe travel. The man of Study II used the automatic feedback to successfully reduce his speech loudness. Automatic feedback can be highly effective in helping persons with multiple disabilities improve their travel and speech performance.
Automatic Speech Recognition: Reliability and Pedagogical Implications for Teaching Pronunciation
ERIC Educational Resources Information Center
Kim, In-Seok
2006-01-01
This study examines the reliability of automatic speech recognition (ASR) software used to teach English pronunciation, focusing on one particular piece of software, "FluSpeak, as a typical example." Thirty-six Korean English as a Foreign Language (EFL) college students participated in an experiment in which they listened to 15 sentences…
Using Automatic Speech Recognition Technology with Elicited Oral Response Testing
ERIC Educational Resources Information Center
Cox, Troy L.; Davies, Randall S.
2012-01-01
This study examined the use of automatic speech recognition (ASR) scored elicited oral response (EOR) tests to assess the speaking ability of English language learners. It also examined the relationship between ASR-scored EOR and other language proficiency measures and the ability of the ASR to rate speakers without bias to gender or native…
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…
Automatically Detecting Likely Edits in Clinical Notes Created Using Automatic Speech Recognition
Lybarger, Kevin; Ostendorf, Mari; Yetisgen, Meliha
2017-01-01
The use of automatic speech recognition (ASR) to create clinical notes has the potential to reduce costs associated with note creation for electronic medical records, but at current system accuracy levels, post-editing by practitioners is needed to ensure note quality. Aiming to reduce the time required to edit ASR transcripts, this paper investigates novel methods for automatic detection of edit regions within the transcripts, including both putative ASR errors but also regions that are targets for cleanup or rephrasing. We create detection models using logistic regression and conditional random field models, exploring a variety of text-based features that consider the structure of clinical notes and exploit the medical context. Different medical text resources are used to improve feature extraction. Experimental results on a large corpus of practitioner-edited clinical notes show that 67% of sentence-level edits and 45% of word-level edits can be detected with a false detection rate of 15%. PMID:29854187
Fidelity of Automatic Speech Processing for Adult and Child Talker Classifications.
VanDam, Mark; Silbert, Noah H
2016-01-01
Automatic speech processing (ASP) has recently been applied to very large datasets of naturalistically collected, daylong recordings of child speech via an audio recorder worn by young children. The system developed by the LENA Research Foundation analyzes children's speech for research and clinical purposes, with special focus on of identifying and tagging family speech dynamics and the at-home acoustic environment from the auditory perspective of the child. A primary issue for researchers, clinicians, and families using the Language ENvironment Analysis (LENA) system is to what degree the segment labels are valid. This classification study evaluates the performance of the computer ASP output against 23 trained human judges who made about 53,000 judgements of classification of segments tagged by the LENA ASP. Results indicate performance consistent with modern ASP such as those using HMM methods, with acoustic characteristics of fundamental frequency and segment duration most important for both human and machine classifications. Results are likely to be important for interpreting and improving ASP output.
Fidelity of Automatic Speech Processing for Adult and Child Talker Classifications
2016-01-01
Automatic speech processing (ASP) has recently been applied to very large datasets of naturalistically collected, daylong recordings of child speech via an audio recorder worn by young children. The system developed by the LENA Research Foundation analyzes children's speech for research and clinical purposes, with special focus on of identifying and tagging family speech dynamics and the at-home acoustic environment from the auditory perspective of the child. A primary issue for researchers, clinicians, and families using the Language ENvironment Analysis (LENA) system is to what degree the segment labels are valid. This classification study evaluates the performance of the computer ASP output against 23 trained human judges who made about 53,000 judgements of classification of segments tagged by the LENA ASP. Results indicate performance consistent with modern ASP such as those using HMM methods, with acoustic characteristics of fundamental frequency and segment duration most important for both human and machine classifications. Results are likely to be important for interpreting and improving ASP output. PMID:27529813
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…
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.
Automatic initial and final segmentation in cleft palate speech of Mandarin speakers.
He, Ling; Liu, Yin; Yin, Heng; Zhang, Junpeng; Zhang, Jing; Zhang, Jiang
2017-01-01
The speech unit segmentation is an important pre-processing step in the analysis of cleft palate speech. In Mandarin, one syllable is composed of two parts: initial and final. In cleft palate speech, the resonance disorders occur at the finals and the voiced initials, while the articulation disorders occur at the unvoiced initials. Thus, the initials and finals are the minimum speech units, which could reflect the characteristics of cleft palate speech disorders. In this work, an automatic initial/final segmentation method is proposed. It is an important preprocessing step in cleft palate speech signal processing. The tested cleft palate speech utterances are collected from the Cleft Palate Speech Treatment Center in the Hospital of Stomatology, Sichuan University, which has the largest cleft palate patients in China. The cleft palate speech data includes 824 speech segments, and the control samples contain 228 speech segments. The syllables are extracted from the speech utterances firstly. The proposed syllable extraction method avoids the training stage, and achieves a good performance for both voiced and unvoiced speech. Then, the syllables are classified into with "quasi-unvoiced" or with "quasi-voiced" initials. Respective initial/final segmentation methods are proposed to these two types of syllables. Moreover, a two-step segmentation method is proposed. The rough locations of syllable and initial/final boundaries are refined in the second segmentation step, in order to improve the robustness of segmentation accuracy. The experiments show that the initial/final segmentation accuracies for syllables with quasi-unvoiced initials are higher than quasi-voiced initials. For the cleft palate speech, the mean time error is 4.4ms for syllables with quasi-unvoiced initials, and 25.7ms for syllables with quasi-voiced initials, and the correct segmentation accuracy P30 for all the syllables is 91.69%. For the control samples, P30 for all the syllables is 91.24%.
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.
Automatic initial and final segmentation in cleft palate speech of Mandarin speakers
Liu, Yin; Yin, Heng; Zhang, Junpeng; Zhang, Jing; Zhang, Jiang
2017-01-01
The speech unit segmentation is an important pre-processing step in the analysis of cleft palate speech. In Mandarin, one syllable is composed of two parts: initial and final. In cleft palate speech, the resonance disorders occur at the finals and the voiced initials, while the articulation disorders occur at the unvoiced initials. Thus, the initials and finals are the minimum speech units, which could reflect the characteristics of cleft palate speech disorders. In this work, an automatic initial/final segmentation method is proposed. It is an important preprocessing step in cleft palate speech signal processing. The tested cleft palate speech utterances are collected from the Cleft Palate Speech Treatment Center in the Hospital of Stomatology, Sichuan University, which has the largest cleft palate patients in China. The cleft palate speech data includes 824 speech segments, and the control samples contain 228 speech segments. The syllables are extracted from the speech utterances firstly. The proposed syllable extraction method avoids the training stage, and achieves a good performance for both voiced and unvoiced speech. Then, the syllables are classified into with “quasi-unvoiced” or with “quasi-voiced” initials. Respective initial/final segmentation methods are proposed to these two types of syllables. Moreover, a two-step segmentation method is proposed. The rough locations of syllable and initial/final boundaries are refined in the second segmentation step, in order to improve the robustness of segmentation accuracy. The experiments show that the initial/final segmentation accuracies for syllables with quasi-unvoiced initials are higher than quasi-voiced initials. For the cleft palate speech, the mean time error is 4.4ms for syllables with quasi-unvoiced initials, and 25.7ms for syllables with quasi-voiced initials, and the correct segmentation accuracy P30 for all the syllables is 91.69%. For the control samples, P30 for all the syllables is 91
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…
Is automatic speech-to-text transcription ready for use in psychological experiments?
Ziman, Kirsten; Heusser, Andrew C; Fitzpatrick, Paxton C; Field, Campbell E; Manning, Jeremy R
2018-04-23
Verbal responses are a convenient and naturalistic way for participants to provide data in psychological experiments (Salzinger, The Journal of General Psychology, 61(1),65-94:1959). However, audio recordings of verbal responses typically require additional processing, such as transcribing the recordings into text, as compared with other behavioral response modalities (e.g., typed responses, button presses, etc.). Further, the transcription process is often tedious and time-intensive, requiring human listeners to manually examine each moment of recorded speech. Here we evaluate the performance of a state-of-the-art speech recognition algorithm (Halpern et al., 2016) in transcribing audio data into text during a list-learning experiment. We compare transcripts made by human annotators to the computer-generated transcripts. Both sets of transcripts matched to a high degree and exhibited similar statistical properties, in terms of the participants' recall performance and recall dynamics that the transcripts captured. This proof-of-concept study suggests that speech-to-text engines could provide a cheap, reliable, and rapid means of automatically transcribing speech data in psychological experiments. Further, our findings open the door for verbal response experiments that scale to thousands of participants (e.g., administered online), as well as a new generation of experiments that decode speech on the fly and adapt experimental parameters based on participants' prior responses.
Effect of speech-intrinsic variations on human and automatic recognition of spoken phonemes.
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.
Speech systems research at Texas Instruments
NASA Technical Reports Server (NTRS)
Doddington, George R.
1977-01-01
An assessment of automatic speech processing technology is presented. Fundamental problems in the development and the deployment of automatic speech processing systems are defined and a technology forecast for speech systems is presented.
Automatic processing of tones and speech stimuli in children with specific language impairment.
Uwer, Ruth; Albrecht, Ronald; von Suchodoletz, W
2002-08-01
It is well known from behavioural experiments that children with specific language impairment (SLI) have difficulties discriminating consonant-vowel (CV) syllables such as /ba/, /da/, and /ga/. Mismatch negativity (MMN) is an auditory event-related potential component that represents the outcome of an automatic comparison process. It could, therefore, be a promising tool for assessing central auditory processing deficits for speech and non-speech stimuli in children with SLI. MMN is typically evoked by occasionally occurring 'deviant' stimuli in a sequence of identical 'standard' sounds. In this study MMN was elicited using simple tone stimuli, which differed in frequency (1000 versus 1200 Hz) and duration (175 versus 100 ms) and to digitized CV syllables which differed in place of articulation (/ba/, /da/, and /ga/) in children with expressive and receptive SLI and healthy control children (n=21 in each group, 46 males and 17 females; age range 5 to 10 years). Mean MMN amplitudes between groups were compared. Additionally, the behavioural discrimination performance was assessed. Children with SLI had attenuated MMN amplitudes to speech stimuli, but there was no significant difference between the two diagnostic subgroups. MMN to tone stimuli did not differ between the groups. Children with SLI made more errors in the discrimination task, but discrimination scores did not correlate with MMN amplitudes. The present data suggest that children with SLI show a specific deficit in automatic discrimination of CV syllables differing in place of articulation, whereas the processing of simple tone differences seems to be unimpaired.
ERIC Educational Resources Information Center
Savage, Robert S.; Frederickson, Norah; Goodwin, Roz; Patni, Ulla; Smith, Nicola; Tuersley, Louise
2005-01-01
In this article, we explore the relationship between rapid automatized naming (RAN) and other cognitive processes among below-average, average, and above-average readers and spellers. Nonsense word reading, phonological awareness, RAN, automaticity of balance, speech perception, and verbal short-term and working memory were measured. Factor…
Automatic concept extraction from spoken medical reports.
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.
Creating speech-synchronized animation.
King, Scott A; Parent, Richard E
2005-01-01
We present a facial model designed primarily to support animated speech. Our facial model takes facial geometry as input and transforms it into a parametric deformable model. The facial model uses a muscle-based parameterization, allowing for easier integration between speech synchrony and facial expressions. Our facial model has a highly deformable lip model that is grafted onto the input facial geometry to provide the necessary geometric complexity needed for creating lip shapes and high-quality renderings. Our facial model also includes a highly deformable tongue model that can represent the shapes the tongue undergoes during speech. We add teeth, gums, and upper palate geometry to complete the inner mouth. To decrease the processing time, we hierarchically deform the facial surface. We also present a method to animate the facial model over time to create animated speech using a model of coarticulation that blends visemes together using dominance functions. We treat visemes as a dynamic shaping of the vocal tract by describing visemes as curves instead of keyframes. We show the utility of the techniques described in this paper by implementing them in a text-to-audiovisual-speech system that creates animation of speech from unrestricted text. The facial and coarticulation models must first be interactively initialized. The system then automatically creates accurate real-time animated speech from the input text. It is capable of cheaply producing tremendous amounts of animated speech with very low resource requirements.
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.
ERIC Educational Resources Information Center
Sidgi, Lina Fathi Sidig; Shaari, Ahmad Jelani
2017-01-01
The use of technology, such as computer-assisted language learning (CALL), is used in teaching and learning in the foreign language classrooms where it is most needed. One promising emerging technology that supports language learning is automatic speech recognition (ASR). Integrating such technology, especially in the instruction of pronunciation…
Automatic Speech Recognition in Air Traffic Control: a Human Factors Perspective
NASA Technical Reports Server (NTRS)
Karlsson, Joakim
1990-01-01
The introduction of Automatic Speech Recognition (ASR) technology into the Air Traffic Control (ATC) system has the potential to improve overall safety and efficiency. However, because ASR technology is inherently a part of the man-machine interface between the user and the system, the human factors issues involved must be addressed. Here, some of the human factors problems are identified and related methods of investigation are presented. Research at M.I.T.'s Flight Transportation Laboratory is being conducted from a human factors perspective, focusing on intelligent parser design, presentation of feedback, error correction strategy design, and optimal choice of input modalities.
NASA Astrophysics Data System (ADS)
Přibil, Jiří; Přibilová, Anna; Frollo, Ivan
2017-12-01
The paper focuses on two methods of evaluation of successfulness of speech signal enhancement recorded in the open-air magnetic resonance imager during phonation for the 3D human vocal tract modeling. The first approach enables to obtain a comparison based on statistical analysis by ANOVA and hypothesis tests. The second method is based on classification by Gaussian mixture models (GMM). The performed experiments have confirmed that the proposed ANOVA and GMM classifiers for automatic evaluation of the speech quality are functional and produce fully comparable results with the standard evaluation based on the listening test method.
Speech Intelligibility Predicted from Neural Entrainment of the Speech Envelope.
Vanthornhout, Jonas; Decruy, Lien; Wouters, Jan; Simon, Jonathan Z; Francart, Tom
2018-04-01
Speech intelligibility is currently measured by scoring how well a person can identify a speech signal. The results of such behavioral measures reflect neural processing of the speech signal, but are also influenced by language processing, motivation, and memory. Very often, electrophysiological measures of hearing give insight in the neural processing of sound. However, in most methods, non-speech stimuli are used, making it hard to relate the results to behavioral measures of speech intelligibility. The use of natural running speech as a stimulus in electrophysiological measures of hearing is a paradigm shift which allows to bridge the gap between behavioral and electrophysiological measures. Here, by decoding the speech envelope from the electroencephalogram, and correlating it with the stimulus envelope, we demonstrate an electrophysiological measure of neural processing of running speech. We show that behaviorally measured speech intelligibility is strongly correlated with our electrophysiological measure. Our results pave the way towards an objective and automatic way of assessing neural processing of speech presented through auditory prostheses, reducing confounds such as attention and cognitive capabilities. We anticipate that our electrophysiological measure will allow better differential diagnosis of the auditory system, and will allow the development of closed-loop auditory prostheses that automatically adapt to individual users.
Goldrick, Matthew; Keshet, Joseph; Gustafson, Erin; Heller, Jordana; Needle, Jeremy
2016-04-01
Traces of the cognitive mechanisms underlying speaking can be found within subtle variations in how we pronounce sounds. While speech errors have traditionally been seen as categorical substitutions of one sound for another, acoustic/articulatory analyses show they partially reflect the intended sound. When "pig" is mispronounced as "big," the resulting /b/ sound differs from correct productions of "big," moving towards intended "pig"-revealing the role of graded sound representations in speech production. Investigating the origins of such phenomena requires detailed estimation of speech sound distributions; this has been hampered by reliance on subjective, labor-intensive manual annotation. Computational methods can address these issues by providing for objective, automatic measurements. We develop a novel high-precision computational approach, based on a set of machine learning algorithms, for measurement of elicited speech. The algorithms are trained on existing manually labeled data to detect and locate linguistically relevant acoustic properties with high accuracy. Our approach is robust, is designed to handle mis-productions, and overall matches the performance of expert coders. It allows us to analyze a very large dataset of speech errors (containing far more errors than the total in the existing literature), illuminating properties of speech sound distributions previously impossible to reliably observe. We argue that this provides novel evidence that two sources both contribute to deviations in speech errors: planning processes specifying the targets of articulation and articulatory processes specifying the motor movements that execute this plan. These findings illustrate how a much richer picture of speech provides an opportunity to gain novel insights into language processing. Copyright © 2016 Elsevier B.V. All rights reserved.
Speech Processing and Recognition (SPaRe)
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
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.
ERIC Educational Resources Information Center
Ashwell, Tim; Elam, Jesse R.
2017-01-01
The ultimate aim of our research project was to use the Google Web Speech API to automate scoring of elicited imitation (EI) tests. However, in order to achieve this goal, we had to take a number of preparatory steps. We needed to assess how accurate this speech recognition tool is in recognizing native speakers' production of the test items; we…
Xiao, Bo; Imel, Zac E; Georgiou, Panayiotis G; Atkins, David C; Narayanan, Shrikanth S
2015-01-01
The technology for evaluating patient-provider interactions in psychotherapy-observational coding-has not changed in 70 years. It is labor-intensive, error prone, and expensive, limiting its use in evaluating psychotherapy in the real world. Engineering solutions from speech and language processing provide new methods for the automatic evaluation of provider ratings from session recordings. The primary data are 200 Motivational Interviewing (MI) sessions from a study on MI training methods with observer ratings of counselor empathy. Automatic Speech Recognition (ASR) was used to transcribe sessions, and the resulting words were used in a text-based predictive model of empathy. Two supporting datasets trained the speech processing tasks including ASR (1200 transcripts from heterogeneous psychotherapy sessions and 153 transcripts and session recordings from 5 MI clinical trials). The accuracy of computationally-derived empathy ratings were evaluated against human ratings for each provider. Computationally-derived empathy scores and classifications (high vs. low) were highly accurate against human-based codes and classifications, with a correlation of 0.65 and F-score (a weighted average of sensitivity and specificity) of 0.86, respectively. Empathy prediction using human transcription as input (as opposed to ASR) resulted in a slight increase in prediction accuracies, suggesting that the fully automatic system with ASR is relatively robust. Using speech and language processing methods, it is possible to generate accurate predictions of provider performance in psychotherapy from audio recordings alone. This technology can support large-scale evaluation of psychotherapy for dissemination and process studies.
The transition to increased automaticity during finger sequence learning in adult males who stutter.
Smits-Bandstra, Sarah; De Nil, Luc; Rochon, Elizabeth
2006-01-01
The present study compared the automaticity levels of persons who stutter (PWS) and persons who do not stutter (PNS) on a practiced finger sequencing task under dual task conditions. Automaticity was defined as the amount of attention required for task performance. Twelve PWS and 12 control subjects practiced finger tapping sequences under single and then dual task conditions. Control subjects performed the sequencing task significantly faster and less variably under single versus dual task conditions while PWS' performance was consistently slow and variable (comparable to the dual task performance of control subjects) under both conditions. Control subjects were significantly more accurate on a colour recognition distracter task than PWS under dual task conditions. These results suggested that control subjects transitioned to quick, accurate and increasingly automatic performance on the sequencing task after practice, while PWS did not. Because most stuttering treatment programs for adults include practice and automatization of new motor speech skills, findings of this finger sequencing study and future studies of speech sequence learning may have important implications for how to maximize stuttering treatment effectiveness. As a result of this activity, the participant will be able to: (1) Define automaticity and explain the importance of dual task paradigms to investigate automaticity; (2) Relate the proposed relationship between motor learning and automaticity as stated by the authors; (3) Summarize the reviewed literature concerning the performance of PWS on dual tasks; and (4) Explain why the ability to transition to automaticity during motor learning may have important clinical implications for stuttering treatment effectiveness.
Reference-free automatic quality assessment of tracheoesophageal speech.
Huang, Andy; Falk, Tiago H; Chan, Wai-Yip; Parsa, Vijay; Doyle, Philip
2009-01-01
Evaluation of the quality of tracheoesophageal (TE) speech using machines instead of human experts can enhance the voice rehabilitation process for patients who have undergone total laryngectomy and voice restoration. Towards the goal of devising a reference-free TE speech quality estimation algorithm, we investigate the efficacy of speech signal features that are used in standard telephone-speech quality assessment algorithms, in conjunction with a recently introduced speech modulation spectrum measure. Tests performed on two TE speech databases demonstrate that the modulation spectral measure and a subset of features in the standard ITU-T P.563 algorithm estimate TE speech quality with better correlation (up to 0.9) than previously proposed features.
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…
Thai Automatic Speech Recognition
2005-01-01
used in an external DARPA evaluation involving medical scenarios between an American Doctor and a naïve monolingual Thai patient. 2. Thai Language... dictionary generation more challenging, and (3) the lack of word segmentation, which calls for automatic segmentation approaches to make n-gram language...requires a dictionary and provides various segmentation algorithms to automatically select suitable segmentations. Here we used a maximal matching
Xiao, Bo; Imel, Zac E.; Georgiou, Panayiotis G.; Atkins, David C.; Narayanan, Shrikanth S.
2015-01-01
The technology for evaluating patient-provider interactions in psychotherapy–observational coding–has not changed in 70 years. It is labor-intensive, error prone, and expensive, limiting its use in evaluating psychotherapy in the real world. Engineering solutions from speech and language processing provide new methods for the automatic evaluation of provider ratings from session recordings. The primary data are 200 Motivational Interviewing (MI) sessions from a study on MI training methods with observer ratings of counselor empathy. Automatic Speech Recognition (ASR) was used to transcribe sessions, and the resulting words were used in a text-based predictive model of empathy. Two supporting datasets trained the speech processing tasks including ASR (1200 transcripts from heterogeneous psychotherapy sessions and 153 transcripts and session recordings from 5 MI clinical trials). The accuracy of computationally-derived empathy ratings were evaluated against human ratings for each provider. Computationally-derived empathy scores and classifications (high vs. low) were highly accurate against human-based codes and classifications, with a correlation of 0.65 and F-score (a weighted average of sensitivity and specificity) of 0.86, respectively. Empathy prediction using human transcription as input (as opposed to ASR) resulted in a slight increase in prediction accuracies, suggesting that the fully automatic system with ASR is relatively robust. Using speech and language processing methods, it is possible to generate accurate predictions of provider performance in psychotherapy from audio recordings alone. This technology can support large-scale evaluation of psychotherapy for dissemination and process studies. PMID:26630392
Primary Progressive Speech Abulia.
Milano, Nicholas J; Heilman, Kenneth M
2015-01-01
Primary progressive aphasia (PPA) is a neurodegenerative disorder characterized by progressive language impairment. The three variants of PPA include the nonfluent/agrammatic, semantic, and logopenic types. The goal of this report is to describe two patients with a loss of speech initiation that was associated with bilateral medial frontal atrophy. Two patients with progressive speech deficits were evaluated and their examinations revealed a paucity of spontaneous speech; however their naming, repetition, reading, and writing were all normal. The patients had no evidence of agrammatism or apraxia of speech but did have impaired speech fluency. In addition to impaired production of propositional spontaneous speech, these patients had impaired production of automatic speech (e.g., reciting the Lord's Prayer) and singing. Structural brain imaging revealed bilateral medial frontal atrophy in both patients. These patients' language deficits are consistent with a PPA, but they are in the pattern of a dynamic aphasia. Whereas the signs-symptoms of dynamic aphasia have been previously described, to our knowledge these are the first cases associated with predominantly bilateral medial frontal atrophy that impaired both propositional and automatic speech. Thus, this profile may represent a new variant of PPA.
Kharlamov, Viktor; Campbell, Kenneth; Kazanina, Nina
2011-11-01
Speech sounds are not always perceived in accordance with their acoustic-phonetic content. For example, an early and automatic process of perceptual repair, which ensures conformity of speech inputs to the listener's native language phonology, applies to individual input segments that do not exist in the native inventory or to sound sequences that are illicit according to the native phonotactic restrictions on sound co-occurrences. The present study with Russian and Canadian English speakers shows that listeners may perceive phonetically distinct and licit sound sequences as equivalent when the native language system provides robust evidence for mapping multiple phonetic forms onto a single phonological representation. In Russian, due to an optional but productive t-deletion process that affects /stn/ clusters, the surface forms [sn] and [stn] may be phonologically equivalent and map to a single phonological form /stn/. In contrast, [sn] and [stn] clusters are usually phonologically distinct in (Canadian) English. Behavioral data from identification and discrimination tasks indicated that [sn] and [stn] clusters were more confusable for Russian than for English speakers. The EEG experiment employed an oddball paradigm with nonwords [asna] and [astna] used as the standard and deviant stimuli. A reliable mismatch negativity response was elicited approximately 100 msec postchange in the English group but not in the Russian group. These findings point to a perceptual repair mechanism that is engaged automatically at a prelexical level to ensure immediate encoding of speech inputs in phonological terms, which in turn enables efficient access to the meaning of a spoken utterance.
Greene, Beth G; Logan, John S; Pisoni, David B
1986-03-01
We present the results of studies designed to measure the segmental intelligibility of eight text-to-speech systems and a natural speech control, using the Modified Rhyme Test (MRT). Results indicated that the voices tested could be grouped into four categories: natural speech, high-quality synthetic speech, moderate-quality synthetic speech, and low-quality synthetic speech. The overall performance of the best synthesis system, DECtalk-Paul, was equivalent to natural speech only in terms of performance on initial consonants. The findings are discussed in terms of recent work investigating the perception of synthetic speech under more severe conditions. Suggestions for future research on improving the quality of synthetic speech are also considered.
GREENE, BETH G.; LOGAN, JOHN S.; PISONI, DAVID B.
2012-01-01
We present the results of studies designed to measure the segmental intelligibility of eight text-to-speech systems and a natural speech control, using the Modified Rhyme Test (MRT). Results indicated that the voices tested could be grouped into four categories: natural speech, high-quality synthetic speech, moderate-quality synthetic speech, and low-quality synthetic speech. The overall performance of the best synthesis system, DECtalk-Paul, was equivalent to natural speech only in terms of performance on initial consonants. The findings are discussed in terms of recent work investigating the perception of synthetic speech under more severe conditions. Suggestions for future research on improving the quality of synthetic speech are also considered. PMID:23225916
Agarwalla, Swapna; Sarma, Kandarpa Kumar
2016-06-01
Automatic Speaker Recognition (ASR) and related issues are continuously evolving as inseparable elements of Human Computer Interaction (HCI). With assimilation of emerging concepts like big data and Internet of Things (IoT) as extended elements of HCI, ASR techniques are found to be passing through a paradigm shift. Oflate, learning based techniques have started to receive greater attention from research communities related to ASR owing to the fact that former possess natural ability to mimic biological behavior and that way aids ASR modeling and processing. The current learning based ASR techniques are found to be evolving further with incorporation of big data, IoT like concepts. Here, in this paper, we report certain approaches based on machine learning (ML) used for extraction of relevant samples from big data space and apply them for ASR using certain soft computing techniques for Assamese speech with dialectal variations. A class of ML techniques comprising of the basic Artificial Neural Network (ANN) in feedforward (FF) and Deep Neural Network (DNN) forms using raw speech, extracted features and frequency domain forms are considered. The Multi Layer Perceptron (MLP) is configured with inputs in several forms to learn class information obtained using clustering and manual labeling. DNNs are also used to extract specific sentence types. Initially, from a large storage, relevant samples are selected and assimilated. Next, a few conventional methods are used for feature extraction of a few selected types. The features comprise of both spectral and prosodic types. These are applied to Recurrent Neural Network (RNN) and Fully Focused Time Delay Neural Network (FFTDNN) structures to evaluate their performance in recognizing mood, dialect, speaker and gender variations in dialectal Assamese speech. The system is tested under several background noise conditions by considering the recognition rates (obtained using confusion matrices and manually) and computation time
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.
Objective speech quality evaluation of real-time speech coders
NASA Astrophysics Data System (ADS)
Viswanathan, V. R.; Russell, W. H.; Huggins, A. W. F.
1984-02-01
This report describes the work performed in two areas: subjective testing of a real-time 16 kbit/s adaptive predictive coder (APC) and objective speech quality evaluation of real-time coders. The speech intelligibility of the APC coder was tested using the Diagnostic Rhyme Test (DRT), and the speech quality was tested using the Diagnostic Acceptability Measure (DAM) test, under eight operating conditions involving channel error, acoustic background noise, and tandem link with two other coders. The test results showed that the DRT and DAM scores of the APC coder equalled or exceeded the corresponding test scores fo the 32 kbit/s CVSD coder. In the area of objective speech quality evaluation, the report describes the development, testing, and validation of a procedure for automatically computing several objective speech quality measures, given only the tape-recordings of the input speech and the corresponding output speech of a real-time speech coder.
Automatic speech recognition in air-ground data link
NASA Technical Reports Server (NTRS)
Armstrong, Herbert B.
1989-01-01
In the present air traffic system, information presented to the transport aircraft cockpit crew may originate from a variety of sources and may be presented to the crew in visual or aural form, either through cockpit instrument displays or, most often, through voice communication. Voice radio communications are the most error prone method for air-ground data link. Voice messages can be misstated or misunderstood and radio frequency congestion can delay or obscure important messages. To prevent proliferation, a multiplexed data link display can be designed to present information from multiple data link sources on a shared cockpit display unit (CDU) or multi-function display (MFD) or some future combination of flight management and data link information. An aural data link which incorporates an automatic speech recognition (ASR) system for crew response offers several advantages over visual displays. The possibility of applying ASR to the air-ground data link was investigated. The first step was to review current efforts in ASR applications in the cockpit and in air traffic control and evaluated their possible data line application. Next, a series of preliminary research questions is to be developed for possible future collaboration.
Text as a Supplement to Speech in Young and Older Adults a)
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
Li, Kan; Príncipe, José C.
2018-01-01
This paper presents a novel real-time dynamic framework for quantifying time-series structure in spoken words using spikes. Audio signals are converted into multi-channel spike trains using a biologically-inspired leaky integrate-and-fire (LIF) spike generator. These spike trains are mapped into a function space of infinite dimension, i.e., a Reproducing Kernel Hilbert Space (RKHS) using point-process kernels, where a state-space model learns the dynamics of the multidimensional spike input using gradient descent learning. This kernelized recurrent system is very parsimonious and achieves the necessary memory depth via feedback of its internal states when trained discriminatively, utilizing the full context of the phoneme sequence. A main advantage of modeling nonlinear dynamics using state-space trajectories in the RKHS is that it imposes no restriction on the relationship between the exogenous input and its internal state. We are free to choose the input representation with an appropriate kernel, and changing the kernel does not impact the system nor the learning algorithm. Moreover, we show that this novel framework can outperform both traditional hidden Markov model (HMM) speech processing as well as neuromorphic implementations based on spiking neural network (SNN), yielding accurate and ultra-low power word spotters. As a proof of concept, we demonstrate its capabilities using the benchmark TI-46 digit corpus for isolated-word automatic speech recognition (ASR) or keyword spotting. Compared to HMM using Mel-frequency cepstral coefficient (MFCC) front-end without time-derivatives, our MFCC-KAARMA offered improved performance. For spike-train front-end, spike-KAARMA also outperformed state-of-the-art SNN solutions. Furthermore, compared to MFCCs, spike trains provided enhanced noise robustness in certain low signal-to-noise ratio (SNR) regime. PMID:29666568
Li, Kan; Príncipe, José C
2018-01-01
This paper presents a novel real-time dynamic framework for quantifying time-series structure in spoken words using spikes. Audio signals are converted into multi-channel spike trains using a biologically-inspired leaky integrate-and-fire (LIF) spike generator. These spike trains are mapped into a function space of infinite dimension, i.e., a Reproducing Kernel Hilbert Space (RKHS) using point-process kernels, where a state-space model learns the dynamics of the multidimensional spike input using gradient descent learning. This kernelized recurrent system is very parsimonious and achieves the necessary memory depth via feedback of its internal states when trained discriminatively, utilizing the full context of the phoneme sequence. A main advantage of modeling nonlinear dynamics using state-space trajectories in the RKHS is that it imposes no restriction on the relationship between the exogenous input and its internal state. We are free to choose the input representation with an appropriate kernel, and changing the kernel does not impact the system nor the learning algorithm. Moreover, we show that this novel framework can outperform both traditional hidden Markov model (HMM) speech processing as well as neuromorphic implementations based on spiking neural network (SNN), yielding accurate and ultra-low power word spotters. As a proof of concept, we demonstrate its capabilities using the benchmark TI-46 digit corpus for isolated-word automatic speech recognition (ASR) or keyword spotting. Compared to HMM using Mel-frequency cepstral coefficient (MFCC) front-end without time-derivatives, our MFCC-KAARMA offered improved performance. For spike-train front-end, spike-KAARMA also outperformed state-of-the-art SNN solutions. Furthermore, compared to MFCCs, spike trains provided enhanced noise robustness in certain low signal-to-noise ratio (SNR) regime.
Wallesch, C W; Brunner, R J; Seemüller, E
1983-12-01
Repetitive phenomena in spontaneous speech were investigated in 30 patients with chronic infarctions of the left hemisphere which included Broca's and/or Wernicke's area and/or the basal ganglia. Perseverations, stereotypies, and echolalias occurred with all types of brain lesions, automatisms and recurring utterances only with those patients, whose infarctions involved Wernicke's area and basal ganglia. These patients also showed more echolalic responses. The results are discussed in view of the role of the basal ganglia as motor program generators.
Alternative Speech Communication System for Persons with Severe Speech Disorders
NASA Astrophysics Data System (ADS)
Selouani, Sid-Ahmed; Sidi Yakoub, Mohammed; O'Shaughnessy, Douglas
2009-12-01
Assistive speech-enabled systems are proposed to help both French and English speaking persons with various speech disorders. The proposed assistive systems use automatic speech recognition (ASR) and speech synthesis in order to enhance the quality of communication. These systems aim at improving the intelligibility of pathologic speech making it as natural as possible and close to the original voice of the speaker. The resynthesized utterances use new basic units, a new concatenating algorithm and a grafting technique to correct the poorly pronounced phonemes. The ASR responses are uttered by the new speech synthesis system in order to convey an intelligible message to listeners. Experiments involving four American speakers with severe dysarthria and two Acadian French speakers with sound substitution disorders (SSDs) are carried out to demonstrate the efficiency of the proposed methods. An improvement of the Perceptual Evaluation of the Speech Quality (PESQ) value of 5% and more than 20% is achieved by the speech synthesis systems that deal with SSD and dysarthria, respectively.
The Relationship Between Speech Production and Speech Perception Deficits in Parkinson's Disease.
De Keyser, Kim; Santens, Patrick; Bockstael, Annelies; Botteldooren, Dick; Talsma, Durk; De Vos, Stefanie; Van Cauwenberghe, Mieke; Verheugen, Femke; Corthals, Paul; De Letter, Miet
2016-10-01
This study investigated the possible relationship between hypokinetic speech production and speech intensity perception in patients with Parkinson's disease (PD). Participants included 14 patients with idiopathic PD and 14 matched healthy controls (HCs) with normal hearing and cognition. First, speech production was objectified through a standardized speech intelligibility assessment, acoustic analysis, and speech intensity measurements. Second, an overall estimation task and an intensity estimation task were addressed to evaluate overall speech perception and speech intensity perception, respectively. Finally, correlation analysis was performed between the speech characteristics of the overall estimation task and the corresponding acoustic analysis. The interaction between speech production and speech intensity perception was investigated by an intensity imitation task. Acoustic analysis and speech intensity measurements demonstrated significant differences in speech production between patients with PD and the HCs. A different pattern in the auditory perception of speech and speech intensity was found in the PD group. Auditory perceptual deficits may influence speech production in patients with PD. The present results suggest a disturbed auditory perception related to an automatic monitoring deficit in PD.
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
ERIC Educational Resources Information Center
Saadatzi, Mohammad Nasser; Pennington, Robert C.; Welch, Karla C.; Graham, James H.; Scott, Renee E.
2017-01-01
In the current study, we examined the effects of an instructional package comprised of an autonomous pedagogical agent, automatic speech recognition, and constant time delay during the instruction of reading sight words aloud to young adults with autism spectrum disorder. We used a concurrent multiple baseline across participants design to…
Automatic detection of articulation disorders in children with cleft lip and palate.
Maier, Andreas; Hönig, Florian; Bocklet, Tobias; Nöth, Elmar; Stelzle, Florian; Nkenke, Emeka; Schuster, Maria
2009-11-01
Speech of children with cleft lip and palate (CLP) is sometimes still disordered even after adequate surgical and nonsurgical therapies. Such speech shows complex articulation disorders, which are usually assessed perceptually, consuming time and manpower. Hence, there is a need for an easy to apply and reliable automatic method. To create a reference for an automatic system, speech data of 58 children with CLP were assessed perceptually by experienced speech therapists for characteristic phonetic disorders at the phoneme level. The first part of the article aims to detect such characteristics by a semiautomatic procedure and the second to evaluate a fully automatic, thus simple, procedure. The methods are based on a combination of speech processing algorithms. The semiautomatic method achieves moderate to good agreement (kappa approximately 0.6) for the detection of all phonetic disorders. On a speaker level, significant correlations between the perceptual evaluation and the automatic system of 0.89 are obtained. The fully automatic system yields a correlation on the speaker level of 0.81 to the perceptual evaluation. This correlation is in the range of the inter-rater correlation of the listeners. The automatic speech evaluation is able to detect phonetic disorders at an experts'level without any additional human postprocessing.
Rapid and automatic speech-specific learning mechanism in human neocortex.
Kimppa, Lilli; Kujala, Teija; Leminen, Alina; Vainio, Martti; Shtyrov, Yury
2015-09-01
A unique feature of human communication system is our ability to rapidly acquire new words and build large vocabularies. However, its neurobiological foundations remain largely unknown. In an electrophysiological study optimally designed to probe this rapid formation of new word memory circuits, we employed acoustically controlled novel word-forms incorporating native and non-native speech sounds, while manipulating the subjects' attention on the input. We found a robust index of neurolexical memory-trace formation: a rapid enhancement of the brain's activation elicited by novel words during a short (~30min) perceptual exposure, underpinned by fronto-temporal cortical networks, and, importantly, correlated with behavioural learning outcomes. Crucially, this neural memory trace build-up took place regardless of focused attention on the input or any pre-existing or learnt semantics. Furthermore, it was found only for stimuli with native-language phonology, but not for acoustically closely matching non-native words. These findings demonstrate a specialised cortical mechanism for rapid, automatic and phonology-dependent formation of neural word memory circuits. Copyright © 2015. Published by Elsevier Inc.
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.
Fully Automatic Speech-Based Analysis of the Semantic Verbal Fluency Task.
König, Alexandra; Linz, Nicklas; Tröger, Johannes; Wolters, Maria; Alexandersson, Jan; Robert, Phillipe
2018-06-08
Semantic verbal fluency (SVF) tests are routinely used in screening for mild cognitive impairment (MCI). In this task, participants name as many items as possible of a semantic category under a time constraint. Clinicians measure task performance manually by summing the number of correct words and errors. More fine-grained variables add valuable information to clinical assessment, but are time-consuming. Therefore, the aim of this study is to investigate whether automatic analysis of the SVF could provide these as accurate as manual and thus, support qualitative screening of neurocognitive impairment. SVF data were collected from 95 older people with MCI (n = 47), Alzheimer's or related dementias (ADRD; n = 24), and healthy controls (HC; n = 24). All data were annotated manually and automatically with clusters and switches. The obtained metrics were validated using a classifier to distinguish HC, MCI, and ADRD. Automatically extracted clusters and switches were highly correlated (r = 0.9) with manually established values, and performed as well on the classification task separating HC from persons with ADRD (area under curve [AUC] = 0.939) and MCI (AUC = 0.758). The results show that it is possible to automate fine-grained analyses of SVF data for the assessment of cognitive decline. © 2018 S. Karger AG, Basel.
Long Term Suboxone™ Emotional Reactivity As Measured by Automatic Detection in Speech
Hill, Edward; Han, David; Dumouchel, Pierre; Dehak, Najim; Quatieri, Thomas; Moehs, Charles; Oscar-Berman, Marlene; Giordano, John; Simpatico, Thomas; Blum, Kenneth
2013-01-01
Addictions to illicit drugs are among the nation’s most critical public health and societal problems. The current opioid prescription epidemic and the need for buprenorphine/naloxone (Suboxone®; SUBX) as an opioid maintenance substance, and its growing street diversion provided impetus to determine affective states (“true ground emotionality”) in long-term SUBX patients. Toward the goal of effective monitoring, we utilized emotion-detection in speech as a measure of “true” emotionality in 36 SUBX patients compared to 44 individuals from the general population (GP) and 33 members of Alcoholics Anonymous (AA). Other less objective studies have investigated emotional reactivity of heroin, methadone and opioid abstinent patients. These studies indicate that current opioid users have abnormal emotional experience, characterized by heightened response to unpleasant stimuli and blunted response to pleasant stimuli. However, this is the first study to our knowledge to evaluate “true ground” emotionality in long-term buprenorphine/naloxone combination (Suboxone™). We found in long-term SUBX patients a significantly flat affect (p<0.01), and they had less self-awareness of being happy, sad, and anxious compared to both the GP and AA groups. We caution definitive interpretation of these seemingly important results until we compare the emotional reactivity of an opioid abstinent control using automatic detection in speech. These findings encourage continued research strategies in SUBX patients to target the specific brain regions responsible for relapse prevention of opioid addiction. PMID:23874860
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.
Use of Computer Speech Technologies To Enhance Learning.
ERIC Educational Resources Information Center
Ferrell, Joe
1999-01-01
Discusses the design of an innovative learning system that uses new technologies for the man-machine interface, incorporating a combination of Automatic Speech Recognition (ASR) and Text To Speech (TTS) synthesis. Highlights include using speech technologies to mimic the attributes of the ideal tutor and design features. (AEF)
López-de-Ipiña, Karmele; Alonso, Jesus-Bernardino; Travieso, Carlos Manuel; Solé-Casals, Jordi; Egiraun, Harkaitz; Faundez-Zanuy, Marcos; Ezeiza, Aitzol; Barroso, Nora; Ecay-Torres, Miriam; Martinez-Lage, Pablo; de Lizardui, Unai Martinez
2013-01-01
The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients. PMID:23698268
Howell, Peter; Sackin, Stevie; Glenn, Kazan
2007-01-01
This program of work is intended to develop automatic recognition procedures to locate and assess stuttered dysfluencies. This and the following article together, develop and test recognizers for repetitions and prolongations. The automatic recognizers classify the speech in two stages: In the first, the speech is segmented and in the second the segments are categorized. The units that are segmented are words. Here assessments by human judges on the speech of 12 children who stutter are described using a corresponding procedure. The accuracy of word boundary placement across judges, categorization of the words as fluent, repetition or prolongation, and duration of the different fluency categories are reported. These measures allow reliable instances of repetitions and prolongations to be selected for training and assessing the recognizers in the subsequent paper. PMID:9328878
Automatic detection of obstructive sleep apnea using speech signals.
Goldshtein, Evgenia; Tarasiuk, Ariel; Zigel, Yaniv
2011-05-01
Obstructive sleep apnea (OSA) is a common disorder associated with anatomical abnormalities of the upper airways that affects 5% of the population. Acoustic parameters may be influenced by the vocal tract structure and soft tissue properties. We hypothesize that speech signal properties of OSA patients will be different than those of control subjects not having OSA. Using speech signal processing techniques, we explored acoustic speech features of 93 subjects who were recorded using a text-dependent speech protocol and a digital audio recorder immediately prior to polysomnography study. Following analysis of the study, subjects were divided into OSA (n=67) and non-OSA (n=26) groups. A Gaussian mixture model-based system was developed to model and classify between the groups; discriminative features such as vocal tract length and linear prediction coefficients were selected using feature selection technique. Specificity and sensitivity of 83% and 79% were achieved for the male OSA and 86% and 84% for the female OSA patients, respectively. We conclude that acoustic features from speech signals during wakefulness can detect OSA patients with good specificity and sensitivity. Such a system can be used as a basis for future development of a tool for OSA screening. © 2011 IEEE
Gowda, Dhananjaya; Airaksinen, Manu; Alku, Paavo
2017-09-01
Recently, a quasi-closed phase (QCP) analysis of speech signals for accurate glottal inverse filtering was proposed. However, the QCP analysis which belongs to the family of temporally weighted linear prediction (WLP) methods uses the conventional forward type of sample prediction. This may not be the best choice especially in computing WLP models with a hard-limiting weighting function. A sample selective minimization of the prediction error in WLP reduces the effective number of samples available within a given window frame. To counter this problem, a modified quasi-closed phase forward-backward (QCP-FB) analysis is proposed, wherein each sample is predicted based on its past as well as future samples thereby utilizing the available number of samples more effectively. Formant detection and estimation experiments on synthetic vowels generated using a physical modeling approach as well as natural speech utterances show that the proposed QCP-FB method yields statistically significant improvements over the conventional linear prediction and QCP methods.
A speech-controlled environmental control system for people with severe dysarthria.
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.
Massively-Parallel Architectures for Automatic Recognition of Visual Speech Signals
1988-10-12
Secusrity Clamifieation, Nlassively-Parallel Architectures for Automa ic Recognitio of Visua, Speech Signals 12. PERSONAL AUTHOR(S) Terrence J...characteristics of speech from tJhe, visual speech signals. Neural networks have been trained on a database of vowels. The rqw images of faces , aligned and...images of faces , aligned and preprocessed, were used as input to these network which were trained to estimate the corresponding envelope of the
Konig, Alexandra; Satt, Aharon; Sorin, Alex; Hoory, Ran; Derreumaux, Alexandre; David, Renaud; Robert, Phillippe H
2018-01-01
Various types of dementia and Mild Cognitive Impairment (MCI) are manifested as irregularities in human speech and language, which have proven to be strong predictors for the disease presence and progress ion. Therefore, automatic speech analytics provided by a mobile application may be a useful tool in providing additional indicators for assessment and detection of early stage dementia and MCI. 165 participants (subjects with subjective cognitive impairment (SCI), MCI patients, Alzheimer's disease (AD) and mixed dementia (MD) patients) were recorded with a mobile application while performing several short vocal cognitive tasks during a regular consultation. These tasks included verbal fluency, picture description, counting down and a free speech task. The voice recordings were processed in two steps: in the first step, vocal markers were extracted using speech signal processing techniques; in the second, the vocal markers were tested to assess their 'power' to distinguish between SCI, MCI, AD and MD. The second step included training automatic classifiers for detecting MCI and AD, based on machine learning methods, and testing the detection accuracy. The fluency and free speech tasks obtain the highest accuracy rates of classifying AD vs. MD vs. MCI vs. SCI. Using the data, we demonstrated classification accuracy as follows: SCI vs. AD = 92% accuracy; SCI vs. MD = 92% accuracy; SCI vs. MCI = 86% accuracy and MCI vs. AD = 86%. Our results indicate the potential value of vocal analytics and the use of a mobile application for accurate automatic differentiation between SCI, MCI and AD. This tool can provide the clinician with meaningful information for assessment and monitoring of people with MCI and AD based on a non-invasive, simple and low-cost method. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Speech fluency profile on different tasks for individuals with Parkinson's disease.
Juste, Fabiola Staróbole; Andrade, Claudia Regina Furquim de
2017-07-20
To characterize the speech fluency profile of patients with Parkinson's disease. Study participants were 40 individuals of both genders aged 40 to 80 years divided into 2 groups: Research Group - RG (20 individuals with diagnosis of Parkinson's disease) and Control Group - CG (20 individuals with no communication or neurological disorders). For all of the participants, three speech samples involving different tasks were collected: monologue, individual reading, and automatic speech. The RG presented a significant larger number of speech disruptions, both stuttering-like and typical dysfluencies, and higher percentage of speech discontinuity in the monologue and individual reading tasks compared with the CG. Both groups presented reduced number of speech disruptions (stuttering-like and typical dysfluencies) in the automatic speech task; the groups presented similar performance in this task. Regarding speech rate, individuals in the RG presented lower number of words and syllables per minute compared with those in the CG in all speech tasks. Participants of the RG presented altered parameters of speech fluency compared with those of the CG; however, this change in fluency cannot be considered a stuttering disorder.
Second Language Learners and Speech Act Comprehension
ERIC Educational Resources Information Center
Holtgraves, Thomas
2007-01-01
Recognizing the specific speech act ( Searle, 1969) that a speaker performs with an utterance is a fundamental feature of pragmatic competence. Past research has demonstrated that native speakers of English automatically recognize speech acts when they comprehend utterances (Holtgraves & Ashley, 2001). The present research examined whether this…
NASA Astrophysics Data System (ADS)
Yang, Zili
2017-07-01
Heart segmentation is an important auxiliary method in the diagnosis of many heart diseases, such as coronary heart disease and atrial fibrillation, and in the planning of tumor radiotherapy. Most of the existing methods for full heart segmentation treat the heart as a whole part and cannot accurately extract the bottom of the heart. In this paper, we propose a new method based on linear gradient model to segment the whole heart from the CT images automatically and accurately. Twelve cases were tested in order to test this method and accurate segmentation results were achieved and identified by clinical experts. The results can provide reliable clinical support.
Automatic Analysis of Pronunciations for Children with Speech Sound Disorders.
Dudy, Shiran; Bedrick, Steven; Asgari, Meysam; Kain, Alexander
2018-07-01
Computer-Assisted Pronunciation Training (CAPT) systems aim to help a child learn the correct pronunciations of words. However, while there are many online commercial CAPT apps, there is no consensus among Speech Language Therapists (SLPs) or non-professionals about which CAPT systems, if any, work well. The prevailing assumption is that practicing with such programs is less reliable and thus does not provide the feedback necessary to allow children to improve their performance. The most common method for assessing pronunciation performance is the Goodness of Pronunciation (GOP) technique. Our paper proposes two new GOP techniques. We have found that pronunciation models that use explicit knowledge about error pronunciation patterns can lead to more accurate classification whether a phoneme was correctly pronounced or not. We evaluate the proposed pronunciation assessment methods against a baseline state of the art GOP approach, and show that the proposed techniques lead to classification performance that is more similar to that of a human expert.
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.
Accurate and consistent automatic seismocardiogram annotation without concurrent ECG.
Laurin, A; Khosrow-Khavar, F; Blaber, A P; Tavakolian, Kouhyar
2016-09-01
Seismocardiography (SCG) is the measurement of vibrations in the sternum caused by the beating of the heart. Precise cardiac mechanical timings that are easily obtained from SCG are critically dependent on accurate identification of fiducial points. So far, SCG annotation has relied on concurrent ECG measurements. An algorithm capable of annotating SCG without the use any other concurrent measurement was designed. We subjected 18 participants to graded lower body negative pressure. We collected ECG and SCG, obtained R peaks from the former, and annotated the latter by hand, using these identified peaks. We also annotated the SCG automatically. We compared the isovolumic moment timings obtained by hand to those obtained using our algorithm. Mean ± confidence interval of the percentage of accurately annotated cardiac cycles were [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] for levels of negative pressure 0, -20, -30, -40, and -50 mmHg. LF/HF ratios, the relative power of low-frequency variations to high-frequency variations in heart beat intervals, obtained from isovolumic moments were also compared to those obtained from R peaks. The mean differences ± confidence interval were [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] for increasing levels of negative pressure. The accuracy and consistency of the algorithm enables the use of SCG as a stand-alone heart monitoring tool in healthy individuals at rest, and could serve as a basis for an eventual application in pathological cases.
Childhood apraxia of speech: A survey of praxis and typical speech characteristics.
Malmenholt, Ann; Lohmander, Anette; McAllister, Anita
2017-07-01
The purpose of this study was to investigate current knowledge of the diagnosis childhood apraxia of speech (CAS) in Sweden and compare speech characteristics and symptoms to those of earlier survey findings in mainly English-speakers. In a web-based questionnaire 178 Swedish speech-language pathologists (SLPs) anonymously answered questions about their perception of typical speech characteristics for CAS. They graded own assessment skills and estimated clinical occurrence. The seven top speech characteristics reported as typical for children with CAS were: inconsistent speech production (85%), sequencing difficulties (71%), oro-motor deficits (63%), vowel errors (62%), voicing errors (61%), consonant cluster deletions (54%), and prosodic disturbance (53%). Motor-programming deficits described as lack of automatization of speech movements were perceived by 82%. All listed characteristics were consistent with the American Speech-Language-Hearing Association (ASHA) consensus-based features, Strand's 10-point checklist, and the diagnostic model proposed by Ozanne. The mode for clinical occurrence was 5%. Number of suspected cases of CAS in the clinical caseload was approximately one new patient/year and SLP. The results support and add to findings from studies of CAS in English-speaking children with similar speech characteristics regarded as typical. Possibly, these findings could contribute to cross-linguistic consensus on CAS characteristics.
Native language shapes automatic neural processing of speech.
Intartaglia, Bastien; White-Schwoch, Travis; Meunier, Christine; Roman, Stéphane; Kraus, Nina; Schön, Daniele
2016-08-01
The development of the phoneme inventory is driven by the acoustic-phonetic properties of one's native language. Neural representation of speech is known to be shaped by language experience, as indexed by cortical responses, and recent studies suggest that subcortical processing also exhibits this attunement to native language. However, most work to date has focused on the differences between tonal and non-tonal languages that use pitch variations to convey phonemic categories. The aim of this cross-language study is to determine whether subcortical encoding of speech sounds is sensitive to language experience by comparing native speakers of two non-tonal languages (French and English). We hypothesized that neural representations would be more robust and fine-grained for speech sounds that belong to the native phonemic inventory of the listener, and especially for the dimensions that are phonetically relevant to the listener such as high frequency components. We recorded neural responses of American English and French native speakers, listening to natural syllables of both languages. Results showed that, independently of the stimulus, American participants exhibited greater neural representation of the fundamental frequency compared to French participants, consistent with the importance of the fundamental frequency to convey stress patterns in English. Furthermore, participants showed more robust encoding and more precise spectral representations of the first formant when listening to the syllable of their native language as compared to non-native language. These results align with the hypothesis that language experience shapes sensory processing of speech and that this plasticity occurs as a function of what is meaningful to a listener. Copyright © 2016 Elsevier Ltd. All rights reserved.
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.
Automatic Title Generation for Spoken Broadcast News
2001-01-01
degrades much less with speech -recognized transcripts. Meanwhile, even though KNN performance not as well as TF.IDF and NBL in terms of F1 metric, it...test corpus of 1006 broadcast news documents, comparing the results over manual transcription to the results over automatically recognized speech . We...use both F1 and the average number of correct title words in the correct order as metric. Overall, the results show that title generation for speech
Presentation video retrieval using automatically recovered slide and spoken text
NASA Astrophysics Data System (ADS)
Cooper, Matthew
2013-03-01
Video is becoming a prevalent medium for e-learning. Lecture videos contain text information in both the presentation slides and lecturer's speech. This paper examines the relative utility of automatically recovered text from these sources for lecture video retrieval. To extract the visual information, we automatically detect slides within the videos and apply optical character recognition to obtain their text. Automatic speech recognition is used similarly to extract spoken text from the recorded audio. We perform controlled experiments with manually created ground truth for both the slide and spoken text from more than 60 hours of lecture video. We compare the automatically extracted slide and spoken text in terms of accuracy relative to ground truth, overlap with one another, and utility for video retrieval. Results reveal that automatically recovered slide text and spoken text contain different content with varying error profiles. Experiments demonstrate that automatically extracted slide text enables higher precision video retrieval than automatically recovered spoken text.
DARPA TIMIT acoustic-phonetic continous speech corpus CD-ROM. NIST speech disc 1-1.1
NASA Astrophysics Data System (ADS)
Garofolo, J. S.; Lamel, L. F.; Fisher, W. M.; Fiscus, J. G.; Pallett, D. S.
1993-02-01
The Texas Instruments/Massachusetts Institute of Technology (TIMIT) corpus of read speech has been designed to provide speech data for the acquisition of acoustic-phonetic knowledge and for the development and evaluation of automatic speech recognition systems. TIMIT contains speech from 630 speakers representing 8 major dialect divisions of American English, each speaking 10 phonetically-rich sentences. The TIMIT corpus includes time-aligned orthographic, phonetic, and word transcriptions, as well as speech waveform data for each spoken sentence. The release of TIMIT contains several improvements over the Prototype CD-ROM released in December, 1988: (1) full 630-speaker corpus, (2) checked and corrected transcriptions, (3) word-alignment transcriptions, (4) NIST SPHERE-headered waveform files and header manipulation software, (5) phonemic dictionary, (6) new test and training subsets balanced for dialectal and phonetic coverage, and (7) more extensive documentation.
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.
A real-time phoneme counting algorithm and application for speech rate monitoring.
Aharonson, Vered; Aharonson, Eran; Raichlin-Levi, Katia; Sotzianu, Aviv; Amir, Ofer; Ovadia-Blechman, Zehava
2017-03-01
Adults who stutter can learn to control and improve their speech fluency by modifying their speaking rate. Existing speech therapy technologies can assist this practice by monitoring speaking rate and providing feedback to the patient, but cannot provide an accurate, quantitative measurement of speaking rate. Moreover, most technologies are too complex and costly to be used for home practice. We developed an algorithm and a smartphone application that monitor a patient's speaking rate in real time and provide user-friendly feedback to both patient and therapist. Our speaking rate computation is performed by a phoneme counting algorithm which implements spectral transition measure extraction to estimate phoneme boundaries. The algorithm is implemented in real time in a mobile application that presents its results in a user-friendly interface. The application incorporates two modes: one provides the patient with visual feedback of his/her speech rate for self-practice and another provides the speech therapist with recordings, speech rate analysis and tools to manage the patient's practice. The algorithm's phoneme counting accuracy was validated on ten healthy subjects who read a paragraph at slow, normal and fast paces, and was compared to manual counting of speech experts. Test-retest and intra-counter reliability were assessed. Preliminary results indicate differences of -4% to 11% between automatic and human phoneme counting. Differences were largest for slow speech. The application can thus provide reliable, user-friendly, real-time feedback for speaking rate control practice. Copyright © 2017 Elsevier Inc. All rights reserved.
Auditory-Motor Processing of Speech Sounds
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
Preliminary Analysis of Automatic Speech Recognition and Synthesis Technology.
1983-05-01
16.311 % a. Seale In/Se"l tAL4 lrs e y i s 2 I ROM men "Ig eddiei, m releerla ons leveltc. Ŗ dots ghoeea INDtISTRtAIJ%6LITARY SPEECH SYNTHESIS PRODUCTS...saquence The SC-01 Suech Syntheszer conftains 64 cf, arent poneme~hs which are accessed try A 6-tht code. 1 - the proper sequ.enti omthnatiors of thoe...connected speech input with widely differing emotional states, diverse accents, and substantial nonperiodic background noise input. As noted previously
Burnett, Greg C [Livermore, CA; Holzrichter, John F [Berkeley, CA; Ng, Lawrence C [Danville, CA
2006-08-08
The present invention is a system and method for characterizing human (or animate) speech voiced excitation functions and acoustic signals, for removing unwanted acoustic noise which often occurs when a speaker uses a microphone in common environments, and for synthesizing personalized or modified human (or other animate) speech upon command from a controller. A low power EM sensor is used to detect the motions of windpipe tissues in the glottal region of the human speech system before, during, and after voiced speech is produced by a user. From these tissue motion measurements, a voiced excitation function can be derived. Further, the excitation function provides speech production information to enhance noise removal from human speech and it enables accurate transfer functions of speech to be obtained. Previously stored excitation and transfer functions can be used for synthesizing personalized or modified human speech. Configurations of EM sensor and acoustic microphone systems are described to enhance noise cancellation and to enable multiple articulator measurements.
Burnett, Greg C.; Holzrichter, John F.; Ng, Lawrence C.
2004-03-23
The present invention is a system and method for characterizing human (or animate) speech voiced excitation functions and acoustic signals, for removing unwanted acoustic noise which often occurs when a speaker uses a microphone in common environments, and for synthesizing personalized or modified human (or other animate) speech upon command from a controller. A low power EM sensor is used to detect the motions of windpipe tissues in the glottal region of the human speech system before, during, and after voiced speech is produced by a user. From these tissue motion measurements, a voiced excitation function can be derived. Further, the excitation function provides speech production information to enhance noise removal from human speech and it enables accurate transfer functions of speech to be obtained. Previously stored excitation and transfer functions can be used for synthesizing personalized or modified human speech. Configurations of EM sensor and acoustic microphone systems are described to enhance noise cancellation and to enable multiple articulator measurements.
Burnett, Greg C.; Holzrichter, John F.; Ng, Lawrence C.
2006-02-14
The present invention is a system and method for characterizing human (or animate) speech voiced excitation functions and acoustic signals, for removing unwanted acoustic noise which often occurs when a speaker uses a microphone in common environments, and for synthesizing personalized or modified human (or other animate) speech upon command from a controller. A low power EM sensor is used to detect the motions of windpipe tissues in the glottal region of the human speech system before, during, and after voiced speech is produced by a user. From these tissue motion measurements, a voiced excitation function can be derived. Further, the excitation function provides speech production information to enhance noise removal from human speech and it enables accurate transfer functions of speech to be obtained. Previously stored excitation and transfer functions can be used for synthesizing personalized or modified human speech. Configurations of EM sensor and acoustic microphone systems are described to enhance noise cancellation and to enable multiple articulator measurements.
Temporal attractors for speech onsets
NASA Astrophysics Data System (ADS)
Port, Robert; Oglesbee, Eric
2003-10-01
When subjects say a single syllable like da in time with a metronome, what is the easiest relationship? Superimposed on the metronome pulse, of course. The second easiest way is probably to locate the syllable halfway between pulses. We tested these hypotheses by having subjects repeat da at both phase angles at a range of metronome rates. The vowel onset (or P-center) was automatically obtained for each token. In-phase targets were produced close to the metronome onset for rates as fast as 3 per second. Antiphase targets were accurate at slow rates (~2/s) but tended to slip to inphase timing with faster metronomes. These results resemble the findings of Haken et al. [Biol. Cybern. 51, 347-356 (1985)] for oscillatory finger motions. Results suggest a strong attractor for speech onsets at zero phase and a weaker attractor at phase 0.5 that may disappear as rate is increased.
Noise-robust speech recognition through auditory feature detection and spike sequence decoding.
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.
Automatic translation among spoken languages
NASA Technical Reports Server (NTRS)
Walter, Sharon M.; Costigan, Kelly
1994-01-01
The Machine Aided Voice Translation (MAVT) system was developed in response to the shortage of experienced military field interrogators with both foreign language proficiency and interrogation skills. Combining speech recognition, machine translation, and speech generation technologies, the MAVT accepts an interrogator's spoken English question and translates it into spoken Spanish. The spoken Spanish response of the potential informant can then be translated into spoken English. Potential military and civilian applications for automatic spoken language translation technology are discussed in this paper.
Larm, Petra; Hongisto, Valtteri
2006-02-01
During the acoustical design of, e.g., auditoria or open-plan offices, it is important to know how speech can be perceived in various parts of the room. Different objective methods have been developed to measure and predict speech intelligibility, and these have been extensively used in various spaces. In this study, two such methods were compared, the speech transmission index (STI) and the speech intelligibility index (SII). Also the simplification of the STI, the room acoustics speech transmission index (RASTI), was considered. These quantities are all based on determining an apparent speech-to-noise ratio on selected frequency bands and summing them using a specific weighting. For comparison, some data were needed on the possible differences of these methods resulting from the calculation scheme and also measuring equipment. Their prediction accuracy was also of interest. Measurements were made in a laboratory having adjustable noise level and absorption, and in a real auditorium. It was found that the measurement equipment, especially the selection of the loudspeaker, can greatly affect the accuracy of the results. The prediction accuracy of the RASTI was found acceptable, if the input values for the prediction are accurately known, even though the studied space was not ideally diffuse.
[The endpoint detection of cough signal in continuous speech].
Yang, Guoqing; Mo, Hongqiang; Li, Wen; Lian, Lianfang; Zheng, Zeguang
2010-06-01
The endpoint detection of cough signal in continuous speech has been researched in order to improve the efficiency and veracity of manual recognition or computer-based automatic recognition. First, using the short time zero crossing ratio(ZCR) for identifying the suspicious coughs and getting the threshold of short time energy based on acoustic characteristics of cough. Then, the short time energy is combined with short time ZCR in order to implement the endpoint detection of cough in continuous speech. To evaluate the effect of the method, first, the virtual number of coughs in each recording was identified by two experienced doctors using the graphical user interface (GUI). Second, the recordings were analyzed by automatic endpoint detection program under Matlab7.0. Finally, the comparison between these two results showed: The error rate of undetected cough is 2.18%, and 98.13% of noise, silence and speech were removed. The way of setting short time energy threshold is robust. The endpoint detection program can remove most speech and noise, thus maintaining a lower rate of error.
Action Unit Models of Facial Expression of Emotion in the Presence of Speech
Shah, Miraj; Cooper, David G.; Cao, Houwei; Gur, Ruben C.; Nenkova, Ani; Verma, Ragini
2014-01-01
Automatic recognition of emotion using facial expressions in the presence of speech poses a unique challenge because talking reveals clues for the affective state of the speaker but distorts the canonical expression of emotion on the face. We introduce a corpus of acted emotion expression where speech is either present (talking) or absent (silent). The corpus is uniquely suited for analysis of the interplay between the two conditions. We use a multimodal decision level fusion classifier to combine models of emotion from talking and silent faces as well as from audio to recognize five basic emotions: anger, disgust, fear, happy and sad. Our results strongly indicate that emotion prediction in the presence of speech from action unit facial features is less accurate when the person is talking. Modeling talking and silent expressions separately and fusing the two models greatly improves accuracy of prediction in the talking setting. The advantages are most pronounced when silent and talking face models are fused with predictions from audio features. In this multi-modal prediction both the combination of modalities and the separate models of talking and silent facial expression of emotion contribute to the improvement. PMID:25525561
Recognizing intentions in infant-directed speech: evidence for universals.
Bryant, Gregory A; Barrett, H Clark
2007-08-01
In all languages studied to date, distinct prosodic contours characterize different intention categories of infant-directed (ID) speech. This vocal behavior likely exists universally as a species-typical trait, but little research has examined whether listeners can accurately recognize intentions in ID speech using only vocal cues, without access to semantic information. We recorded native-English-speaking mothers producing four intention categories of utterances (prohibition, approval, comfort, and attention) as both ID and adult-directed (AD) speech, and we then presented the utterances to Shuar adults (South American hunter-horticulturalists). Shuar subjects were able to reliably distinguish ID from AD speech and were able to reliably recognize the intention categories in both types of speech, although performance was significantly better with ID speech. This is the first demonstration that adult listeners in an indigenous, nonindustrialized, and nonliterate culture can accurately infer intentions from both ID speech and AD speech in a language they do not speak.
Audio-video feature correlation: faces and speech
NASA Astrophysics Data System (ADS)
Durand, Gwenael; Montacie, Claude; Caraty, Marie-Jose; Faudemay, Pascal
1999-08-01
This paper presents a study of the correlation of features automatically extracted from the audio stream and the video stream of audiovisual documents. In particular, we were interested in finding out whether speech analysis tools could be combined with face detection methods, and to what extend they should be combined. A generic audio signal partitioning algorithm as first used to detect Silence/Noise/Music/Speech segments in a full length movie. A generic object detection method was applied to the keyframes extracted from the movie in order to detect the presence or absence of faces. The correlation between the presence of a face in the keyframes and of the corresponding voice in the audio stream was studied. A third stream, which is the script of the movie, is warped on the speech channel in order to automatically label faces appearing in the keyframes with the name of the corresponding character. We naturally found that extracted audio and video features were related in many cases, and that significant benefits can be obtained from the joint use of audio and video analysis methods.
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.
Automated Intelligibility Assessment of Pathological Speech Using Phonological Features
NASA Astrophysics Data System (ADS)
Middag, Catherine; Martens, Jean-Pierre; Van Nuffelen, Gwen; De Bodt, Marc
2009-12-01
It is commonly acknowledged that word or phoneme intelligibility is an important criterion in the assessment of the communication efficiency of a pathological speaker. People have therefore put a lot of effort in the design of perceptual intelligibility rating tests. These tests usually have the drawback that they employ unnatural speech material (e.g., nonsense words) and that they cannot fully exclude errors due to listener bias. Therefore, there is a growing interest in the application of objective automatic speech recognition technology to automate the intelligibility assessment. Current research is headed towards the design of automated methods which can be shown to produce ratings that correspond well with those emerging from a well-designed and well-performed perceptual test. In this paper, a novel methodology that is built on previous work (Middag et al., 2008) is presented. It utilizes phonological features, automatic speech alignment based on acoustic models that were trained on normal speech, context-dependent speaker feature extraction, and intelligibility prediction based on a small model that can be trained on pathological speech samples. The experimental evaluation of the new system reveals that the root mean squared error of the discrepancies between perceived and computed intelligibilities can be as low as 8 on a scale of 0 to 100.
How should a speech recognizer work?
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.
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.
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.
Children's perception of their synthetically corrected speech production.
Strömbergsson, Sofia; Wengelin, Asa; House, David
2014-06-01
We explore children's perception of their own speech - in its online form, in its recorded form, and in synthetically modified forms. Children with phonological disorder (PD) and children with typical speech and language development (TD) performed tasks of evaluating accuracy of the different types of speech stimuli, either immediately after having produced the utterance or after a delay. In addition, they performed a task designed to assess their ability to detect synthetic modification. Both groups showed high performance in tasks involving evaluation of other children's speech, whereas in tasks of evaluating one's own speech, the children with PD were less accurate than their TD peers. The children with PD were less sensitive to misproductions in immediate conjunction with their production of an utterance, and more accurate after a delay. Within-category modification often passed undetected, indicating a satisfactory quality of the generated speech. Potential clinical benefits of using corrective re-synthesis are discussed.
Evaluation of an Expert System for the Generation of Speech and Language Therapy Plans
López-Nores, Martín; García-Duque, Jorge; Pazos-Arias, José J; Arévalo-Lucero, Daysi
2016-01-01
Background Speech and language pathologists (SLPs) deal with a wide spectrum of disorders, arising from many different conditions, that affect voice, speech, language, and swallowing capabilities in different ways. Therefore, the outcomes of Speech and Language Therapy (SLT) are highly dependent on the accurate, consistent, and complete design of personalized therapy plans. However, SLPs often have very limited time to work with their patients and to browse the large (and growing) catalogue of activities and specific exercises that can be put into therapy plans. As a consequence, many plans are suboptimal and fail to address the specific needs of each patient. Objective We aimed to evaluate an expert system that automatically generates plans for speech and language therapy, containing semiannual activities in the five areas of hearing, oral structure and function, linguistic formulation, expressive language and articulation, and receptive language. The goal was to assess whether the expert system speeds up the SLPs’ work and leads to more accurate, consistent, and complete therapy plans for their patients. Methods We examined the evaluation results of the SPELTA expert system in supporting the decision making of 4 SLPs treating children in three special education institutions in Ecuador. The expert system was first trained with data from 117 cases, including medical data; diagnosis for voice, speech, language and swallowing capabilities; and therapy plans created manually by the SLPs. It was then used to automatically generate new therapy plans for 13 new patients. The SLPs were finally asked to evaluate the accuracy, consistency, and completeness of those plans. A four-fold cross-validation experiment was also run on the original corpus of 117 cases in order to assess the significance of the results. Results The evaluation showed that 87% of the outputs provided by the SPELTA expert system were considered valid therapy plans for the different areas. The SLPs
Evaluation of an Expert System for the Generation of Speech and Language Therapy Plans.
Robles-Bykbaev, Vladimir; López-Nores, Martín; García-Duque, Jorge; Pazos-Arias, José J; Arévalo-Lucero, Daysi
2016-07-01
Speech and language pathologists (SLPs) deal with a wide spectrum of disorders, arising from many different conditions, that affect voice, speech, language, and swallowing capabilities in different ways. Therefore, the outcomes of Speech and Language Therapy (SLT) are highly dependent on the accurate, consistent, and complete design of personalized therapy plans. However, SLPs often have very limited time to work with their patients and to browse the large (and growing) catalogue of activities and specific exercises that can be put into therapy plans. As a consequence, many plans are suboptimal and fail to address the specific needs of each patient. We aimed to evaluate an expert system that automatically generates plans for speech and language therapy, containing semiannual activities in the five areas of hearing, oral structure and function, linguistic formulation, expressive language and articulation, and receptive language. The goal was to assess whether the expert system speeds up the SLPs' work and leads to more accurate, consistent, and complete therapy plans for their patients. We examined the evaluation results of the SPELTA expert system in supporting the decision making of 4 SLPs treating children in three special education institutions in Ecuador. The expert system was first trained with data from 117 cases, including medical data; diagnosis for voice, speech, language and swallowing capabilities; and therapy plans created manually by the SLPs. It was then used to automatically generate new therapy plans for 13 new patients. The SLPs were finally asked to evaluate the accuracy, consistency, and completeness of those plans. A four-fold cross-validation experiment was also run on the original corpus of 117 cases in order to assess the significance of the results. The evaluation showed that 87% of the outputs provided by the SPELTA expert system were considered valid therapy plans for the different areas. The SLPs rated the overall accuracy, consistency
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…
NASA Astrophysics Data System (ADS)
He, Wantao; Li, Zhongwei; Zhong, Kai; Shi, Yusheng; Zhao, Can; Cheng, Xu
2014-11-01
Fast and precise 3D inspection system is in great demand in modern manufacturing processes. At present, the available sensors have their own pros and cons, and hardly exist an omnipotent sensor to handle the complex inspection task in an accurate and effective way. The prevailing solution is integrating multiple sensors and taking advantages of their strengths. For obtaining a holistic 3D profile, the data from different sensors should be registrated into a coherent coordinate system. However, some complex shape objects own thin wall feather such as blades, the ICP registration method would become unstable. Therefore, it is very important to calibrate the extrinsic parameters of each sensor in the integrated measurement system. This paper proposed an accurate and automatic extrinsic parameter calibration method for blade measurement system integrated by different optical sensors. In this system, fringe projection sensor (FPS) and conoscopic holography sensor (CHS) is integrated into a multi-axis motion platform, and the sensors can be optimally move to any desired position at the object's surface. In order to simple the calibration process, a special calibration artifact is designed according to the characteristics of the two sensors. An automatic registration procedure based on correlation and segmentation is used to realize the artifact datasets obtaining by FPS and CHS rough alignment without any manual operation and data pro-processing, and then the Generalized Gauss-Markoff model is used to estimate the optimization transformation parameters. The experiments show the measurement result of a blade, where several sampled patches are merged into one point cloud, and it verifies the performance of the proposed method.
2017-03-01
the Center for Technology Enhanced Language Learning (CTELL), a research cell in the Department of Foreign Languages, United States Military Academy...models for automatic speech recognition (ASR), and to, thereby, investigate the utility of ASR in pedagogical technology . The corpus is a sample of...lexical resources, language technology 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF
The speech perception skills of children with and without speech sound disorder.
Hearnshaw, Stephanie; Baker, Elise; Munro, Natalie
To investigate whether Australian-English speaking children with and without speech sound disorder (SSD) differ in their overall speech perception accuracy. Additionally, to investigate differences in the perception of specific phonemes and the association between speech perception and speech production skills. Twenty-five Australian-English speaking children aged 48-60 months participated in this study. The SSD group included 12 children and the typically developing (TD) group included 13 children. Children completed routine speech and language assessments in addition to an experimental Australian-English lexical and phonetic judgement task based on Rvachew's Speech Assessment and Interactive Learning System (SAILS) program (Rvachew, 2009). This task included eight words across four word-initial phonemes-/k, ɹ, ʃ, s/. Children with SSD showed significantly poorer perceptual accuracy on the lexical and phonetic judgement task compared with TD peers. The phonemes /ɹ/ and /s/ were most frequently perceived in error across both groups. Additionally, the phoneme /ɹ/ was most commonly produced in error. There was also a positive correlation between overall speech perception and speech production scores. Children with SSD perceived speech less accurately than their typically developing peers. The findings suggest that an Australian-English variation of a lexical and phonetic judgement task similar to the SAILS program is promising and worthy of a larger scale study. Copyright © 2017 Elsevier Inc. All rights reserved.
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
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.
Vasconcelos, Maria J M; Ventura, Sandra M R; Freitas, Diamantino R S; Tavares, João Manuel R S
2012-03-01
The morphological and dynamic characterisation of the vocal tract during speech production has been gaining greater attention due to the motivation of the latest improvements in magnetic resonance (MR) imaging; namely, with the use of higher magnetic fields, such as 3.0 Tesla. In this work, the automatic study of the vocal tract from 3.0 Tesla MR images was assessed through the application of statistical deformable models. Therefore, the primary goal focused on the analysis of the shape of the vocal tract during the articulation of European Portuguese sounds, followed by the evaluation of the results concerning the automatic segmentation, i.e. identification of the vocal tract in new MR images. In what concerns speech production, this is the first attempt to automatically characterise and reconstruct the vocal tract shape of 3.0 Tesla MR images by using deformable models; particularly, by using active and appearance shape models. The achieved results clearly evidence the adequacy and advantage of the automatic analysis of the 3.0 Tesla MR images of these deformable models in order to extract the vocal tract shape and assess the involved articulatory movements. These achievements are mostly required, for example, for a better knowledge of speech production, mainly of patients suffering from articulatory disorders, and to build enhanced speech synthesizer models.
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.
Segmental intelligibility of synthetic speech produced by rule.
Logan, J S; Greene, B G; Pisoni, D B
1989-08-01
This paper reports the results of an investigation that employed the modified rhyme test (MRT) to measure the segmental intelligibility of synthetic speech generated automatically by rule. Synthetic speech produced by ten text-to-speech systems was studied and compared to natural speech. A variation of the standard MRT was also used to study the effects of response set size on perceptual confusions. Results indicated that the segmental intelligibility scores formed a continuum. Several systems displayed very high levels of performance that were close to or equal to scores obtained with natural speech; other systems displayed substantially worse performance compared to natural speech. The overall performance of the best system, DECtalk--Paul, was equivalent to the data obtained with natural speech for consonants in syllable-initial position. The findings from this study are discussed in terms of the use of a set of standardized procedures for measuring intelligibility of synthetic speech under controlled laboratory conditions. Recent work investigating the perception of synthetic speech under more severe conditions in which greater demands are made on the listener's processing resources is also considered. The wide range of intelligibility scores obtained in the present study demonstrates important differences in perception and suggests that not all synthetic speech is perceptually equivalent to the listener.
Segmental intelligibility of synthetic speech produced by rule
Logan, John S.; Greene, Beth G.; Pisoni, David B.
2012-01-01
This paper reports the results of an investigation that employed the modified rhyme test (MRT) to measure the segmental intelligibility of synthetic speech generated automatically by rule. Synthetic speech produced by ten text-to-speech systems was studied and compared to natural speech. A variation of the standard MRT was also used to study the effects of response set size on perceptual confusions. Results indicated that the segmental intelligibility scores formed a continuum. Several systems displayed very high levels of performance that were close to or equal to scores obtained with natural speech; other systems displayed substantially worse performance compared to natural speech. The overall performance of the best system, DECtalk—Paul, was equivalent to the data obtained with natural speech for consonants in syllable-initial position. The findings from this study are discussed in terms of the use of a set of standardized procedures for measuring intelligibility of synthetic speech under controlled laboratory conditions. Recent work investigating the perception of synthetic speech under more severe conditions in which greater demands are made on the listener’s processing resources is also considered. The wide range of intelligibility scores obtained in the present study demonstrates important differences in perception and suggests that not all synthetic speech is perceptually equivalent to the listener. PMID:2527884
Methods and apparatus for non-acoustic speech characterization and recognition
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.
ERIC Educational Resources Information Center
Pattamadilok, Chotiga; Nelis, Aubéline; Kolinsky, Régine
2014-01-01
Studies on proficient readers showed that speech processing is affected by knowledge of the orthographic code. Yet, the automaticity of the orthographic influence depends on task demand. Here, we addressed this automaticity issue in normal and dyslexic adult readers by comparing the orthographic effects obtained in two speech processing tasks that…
Tuning time-frequency methods for the detection of metered HF speech
NASA Astrophysics Data System (ADS)
Nelson, Douglas J.; Smith, Lawrence H.
2002-12-01
Speech is metered if the stresses occur at a nearly regular rate. Metered speech is common in poetry, and it can occur naturally in speech, if the speaker is spelling a word or reciting words or numbers from a list. In radio communications, the CQ request, call sign and other codes are frequently metered. In tactical communications and air traffic control, location, heading and identification codes may be metered. Moreover metering may be expected to survive even in HF communications, which are corrupted by noise, interference and mistuning. For this environment, speech recognition and conventional machine-based methods are not effective. We describe Time-Frequency methods which have been adapted successfully to the problem of mitigation of HF signal conditions and detection of metered speech. These methods are based on modeled time and frequency correlation properties of nearly harmonic functions. We derive these properties and demonstrate a performance gain over conventional correlation and spectral methods. Finally, in addressing the problem of HF single sideband (SSB) communications, the problems of carrier mistuning, interfering signals, such as manual Morse, and fast automatic gain control (AGC) must be addressed. We demonstrate simple methods which may be used to blindly mitigate mistuning and narrowband interference, and effectively invert the fast automatic gain function.
NASA Astrophysics Data System (ADS)
Kong, Zhenglun; Luo, Junyi; Xu, Shengpu; Li, Ting
2018-02-01
Image segmentation plays an important role in medical science. One application is multimodality imaging, especially the fusion of structural imaging with functional imaging, which includes CT, MRI and new types of imaging technology such as optical imaging to obtain functional images. The fusion process require precisely extracted structural information, in order to register the image to it. Here we used image enhancement, morphometry methods to extract the accurate contours of different tissues such as skull, cerebrospinal fluid (CSF), grey matter (GM) and white matter (WM) on 5 fMRI head image datasets. Then we utilized convolutional neural network to realize automatic segmentation of images in deep learning way. Such approach greatly reduced the processing time compared to manual and semi-automatic segmentation and is of great importance in improving speed and accuracy as more and more samples being learned. The contours of the borders of different tissues on all images were accurately extracted and 3D visualized. This can be used in low-level light therapy and optical simulation software such as MCVM. We obtained a precise three-dimensional distribution of brain, which offered doctors and researchers quantitative volume data and detailed morphological characterization for personal precise medicine of Cerebral atrophy/expansion. We hope this technique can bring convenience to visualization medical and personalized medicine.
An acoustic comparison of two women's infant- and adult-directed speech
NASA Astrophysics Data System (ADS)
Andruski, Jean; Katz-Gershon, Shiri
2003-04-01
In addition to having prosodic characteristics that are attractive to infant listeners, infant-directed (ID) speech shares certain characteristics of adult-directed (AD) clear speech, such as increased acoustic distance between vowels, that might be expected to make ID speech easier for adults to perceive in noise than AD conversational speech. However, perceptual tests of two women's ID productions by Andruski and Bessega [J. Acoust. Soc. Am. 112, 2355] showed that is not always the case. In a word identification task that compared ID speech with AD clear and conversational speech, one speaker's ID productions were less well-identified than AD clear speech, but better identified than AD conversational speech. For the second woman, ID speech was the least accurately identified of the three speech registers. For both speakers, hard words (infrequent words with many lexical neighbors) were also at an increased disadvantage relative to easy words (frequent words with few lexical neighbors) in speech registers that were less accurately perceived. This study will compare several acoustic properties of these women's productions, including pitch and formant-frequency characteristics. Results of the acoustic analyses will be examined with the original perceptual results to suggest reasons for differences in listener's accuracy in identifying these two women's ID speech in noise.
Kraaijenga, S A C; Oskam, I M; van Son, R J J H; Hamming-Vrieze, O; Hilgers, F J M; van den Brekel, M W M; van der Molen, L
2016-04-01
Assessment of long-term objective and subjective voice, speech, articulation, and quality of life in patients with head and neck cancer (HNC) treated with concurrent chemoradiotherapy (CRT) for advanced, stage IV disease. Twenty-two disease-free survivors, treated with cisplatin-based CRT for inoperable HNC (1999-2004), were evaluated at 10-years post-treatment. A standard Dutch text was recorded. Perceptual analysis of voice, speech, and articulation was conducted by two expert listeners (SLPs). Also an experimental expert system based on automatic speech recognition was used. Patients' perception of voice and speech and related quality of life was assessed with the Voice Handicap Index (VHI) and Speech Handicap Index (SHI) questionnaires. At a median follow-up of 11-years, perceptual evaluation showed abnormal scores in up to 64% of cases, depending on the outcome parameter analyzed. Automatic assessment of voice and speech parameters correlated moderate to strong with perceptual outcome scores. Patient-reported problems with voice (VHI>15) and speech (SHI>6) in daily life were present in 68% and 77% of patients, respectively. Patients treated with IMRT showed significantly less impairment compared to those treated with conventional radiotherapy. More than 10-years after organ-preservation treatment, voice and speech problems are common in this patient cohort, as assessed with perceptual evaluation, automatic speech recognition, and with validated structured questionnaires. There were fewer complaints in patients treated with IMRT than with conventional radiotherapy. Copyright © 2016 Elsevier Ltd. All rights reserved.
Random Deep Belief Networks for Recognizing Emotions from Speech Signals.
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
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 probabilistic union model with automatic order selection for noisy speech recognition.
Jancovic, P; Ming, J
2001-09-01
A critical issue in exploiting the potential of the sub-band-based approach to robust speech recognition is the method of combining the sub-band observations, for selecting the bands unaffected by noise. A new method for this purpose, i.e., the probabilistic union model, was recently introduced. This model has been shown to be capable of dealing with band-limited corruption, requiring no knowledge about the band position and statistical distribution of the noise. A parameter within the model, which we call its order, gives the best results when it equals the number of noisy bands. Since this information may not be available in practice, in this paper we introduce an automatic algorithm for selecting the order, based on the state duration pattern generated by the hidden Markov model (HMM). The algorithm has been tested on the TIDIGITS database corrupted by various types of additive band-limited noise with unknown noisy bands. The results have shown that the union model equipped with the new algorithm can achieve a recognition performance similar to that achieved when the number of noisy bands is known. The results show a very significant improvement over the traditional full-band model, without requiring prior information on either the position or the number of noisy bands. The principle of the algorithm for selecting the order based on state duration may also be applied to other sub-band combination methods.
DETECTION AND IDENTIFICATION OF SPEECH SOUNDS USING CORTICAL ACTIVITY PATTERNS
Centanni, T.M.; Sloan, A.M.; Reed, A.C.; Engineer, C.T.; Rennaker, R.; Kilgard, M.P.
2014-01-01
We have developed a classifier capable of locating and identifying speech sounds using activity from rat auditory cortex with an accuracy equivalent to behavioral performance without the need to specify the onset time of the speech sounds. This classifier can identify speech sounds from a large speech set within 40 ms of stimulus presentation. To compare the temporal limits of the classifier to behavior, we developed a novel task that requires rats to identify individual consonant sounds from a stream of distracter consonants. The classifier successfully predicted the ability of rats to accurately identify speech sounds for syllable presentation rates up to 10 syllables per second (up to 17.9 ± 1.5 bits/sec), which is comparable to human performance. Our results demonstrate that the spatiotemporal patterns generated in primary auditory cortex can be used to quickly and accurately identify consonant sounds from a continuous speech stream without prior knowledge of the stimulus onset times. Improved understanding of the neural mechanisms that support robust speech processing in difficult listening conditions could improve the identification and treatment of a variety of speech processing disorders. PMID:24286757
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.
Processing of speech signals for physical and sensory disabilities.
Levitt, H
1995-01-01
Assistive technology involving voice communication is used primarily by people who are deaf, hard of hearing, or who have speech and/or language disabilities. It is also used to a lesser extent by people with visual or motor disabilities. A very wide range of devices has been developed for people with hearing loss. These devices can be categorized not only by the modality of stimulation [i.e., auditory, visual, tactile, or direct electrical stimulation of the auditory nerve (auditory-neural)] but also in terms of the degree of speech processing that is used. At least four such categories can be distinguished: assistive devices (a) that are not designed specifically for speech, (b) that take the average characteristics of speech into account, (c) that process articulatory or phonetic characteristics of speech, and (d) that embody some degree of automatic speech recognition. Assistive devices for people with speech and/or language disabilities typically involve some form of speech synthesis or symbol generation for severe forms of language disability. Speech synthesis is also used in text-to-speech systems for sightless persons. Other applications of assistive technology involving voice communication include voice control of wheelchairs and other devices for people with mobility disabilities. Images Fig. 4 PMID:7479816
Processing of Speech Signals for Physical and Sensory Disabilities
NASA Astrophysics Data System (ADS)
Levitt, Harry
1995-10-01
Assistive technology involving voice communication is used primarily by people who are deaf, hard of hearing, or who have speech and/or language disabilities. It is also used to a lesser extent by people with visual or motor disabilities. A very wide range of devices has been developed for people with hearing loss. These devices can be categorized not only by the modality of stimulation [i.e., auditory, visual, tactile, or direct electrical stimulation of the auditory nerve (auditory-neural)] but also in terms of the degree of speech processing that is used. At least four such categories can be distinguished: assistive devices (a) that are not designed specifically for speech, (b) that take the average characteristics of speech into account, (c) that process articulatory or phonetic characteristics of speech, and (d) that embody some degree of automatic speech recognition. Assistive devices for people with speech and/or language disabilities typically involve some form of speech synthesis or symbol generation for severe forms of language disability. Speech synthesis is also used in text-to-speech systems for sightless persons. Other applications of assistive technology involving voice communication include voice control of wheelchairs and other devices for people with mobility disabilities.
Parker, Mark; Cunningham, Stuart; Enderby, Pam; Hawley, Mark; Green, Phil
2006-01-01
The STARDUST project developed robust computer speech recognizers for use by eight people with severe dysarthria and concomitant physical disability to access assistive technologies. Independent computer speech recognizers trained with normal speech are of limited functional use by those with severe dysarthria due to limited and inconsistent proximity to "normal" articulatory patterns. Severe dysarthric output may also be characterized by a small mass of distinguishable phonetic tokens making the acoustic differentiation of target words difficult. Speaker dependent computer speech recognition using Hidden Markov Models was achieved by the identification of robust phonetic elements within the individual speaker output patterns. A new system of speech training using computer generated visual and auditory feedback reduced the inconsistent production of key phonetic tokens over time.
Speech rate in Parkinson's disease: A controlled study.
Martínez-Sánchez, F; Meilán, J J G; Carro, J; Gómez Íñiguez, C; Millian-Morell, L; Pujante Valverde, I M; López-Alburquerque, T; López, D E
2016-09-01
Speech disturbances will affect most patients with Parkinson's disease (PD) over the course of the disease. The origin and severity of these symptoms are of clinical and diagnostic interest. To evaluate the clinical pattern of speech impairment in PD patients and identify significant differences in speech rate and articulation compared to control subjects. Speech rate and articulation in a reading task were measured using an automatic analytical method. A total of 39 PD patients in the 'on' state and 45 age-and sex-matched asymptomatic controls participated in the study. None of the patients experienced dyskinesias or motor fluctuations during the test. The patients with PD displayed a significant reduction in speech and articulation rates; there were no significant correlations between the studied speech parameters and patient characteristics such as L-dopa dose, duration of the disorder, age, and UPDRS III scores and Hoehn & Yahr scales. Patients with PD show a characteristic pattern of declining speech rate. These results suggest that in PD, disfluencies are the result of the movement disorder affecting the physiology of speech production systems. Copyright © 2014 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.
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…
A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops.
Bengochea-Guevara, José M; Andújar, Dionisio; Sanchez-Sardana, Francisco L; Cantuña, Karla; Ribeiro, Angela
2017-12-24
Crop monitoring is an essential practice within the field of precision agriculture since it is based on observing, measuring and properly responding to inter- and intra-field variability. In particular, "on ground crop inspection" potentially allows early detection of certain crop problems or precision treatment to be carried out simultaneously with pest detection. "On ground monitoring" is also of great interest for woody crops. This paper explores the development of a low-cost crop monitoring system that can automatically create accurate 3D models (clouds of coloured points) of woody crop rows. The system consists of a mobile platform that allows the easy acquisition of information in the field at an average speed of 3 km/h. The platform, among others, integrates an RGB-D sensor that provides RGB information as well as an array with the distances to the objects closest to the sensor. The RGB-D information plus the geographical positions of relevant points, such as the starting and the ending points of the row, allow the generation of a 3D reconstruction of a woody crop row in which all the points of the cloud have a geographical location as well as the RGB colour values. The proposed approach for the automatic 3D reconstruction is not limited by the size of the sampled space and includes a method for the removal of the drift that appears in the reconstruction of large crop rows.
A Low-Cost Approach to Automatically Obtain Accurate 3D Models of Woody Crops
Andújar, Dionisio; Sanchez-Sardana, Francisco L.; Cantuña, Karla
2017-01-01
Crop monitoring is an essential practice within the field of precision agriculture since it is based on observing, measuring and properly responding to inter- and intra-field variability. In particular, “on ground crop inspection” potentially allows early detection of certain crop problems or precision treatment to be carried out simultaneously with pest detection. “On ground monitoring” is also of great interest for woody crops. This paper explores the development of a low-cost crop monitoring system that can automatically create accurate 3D models (clouds of coloured points) of woody crop rows. The system consists of a mobile platform that allows the easy acquisition of information in the field at an average speed of 3 km/h. The platform, among others, integrates an RGB-D sensor that provides RGB information as well as an array with the distances to the objects closest to the sensor. The RGB-D information plus the geographical positions of relevant points, such as the starting and the ending points of the row, allow the generation of a 3D reconstruction of a woody crop row in which all the points of the cloud have a geographical location as well as the RGB colour values. The proposed approach for the automatic 3D reconstruction is not limited by the size of the sampled space and includes a method for the removal of the drift that appears in the reconstruction of large crop rows. PMID:29295536
Burnett, Greg C.; Holzrichter, John F.; Ng, Lawrence C.
2006-04-25
The present invention is a system and method for characterizing human (or animate) speech voiced excitation functions and acoustic signals, for removing unwanted acoustic noise which often occurs when a speaker uses a microphone in common environments, and for synthesizing personalized or modified human (or other animate) speech upon command from a controller. A low power EM sensor is used to detect the motions of windpipe tissues in the glottal region of the human speech system before, during, and after voiced speech is produced by a user. From these tissue motion measurements, a voiced excitation function can be derived. Further, the excitation function provides speech production information to enhance noise removal from human speech and it enables accurate transfer functions of speech to be obtained. Previously stored excitation and transfer functions can be used for synthesizing personalized or modified human speech. Configurations of EM sensor and acoustic microphone systems are described to enhance noise cancellation and to enable multiple articulator measurements.
Hisagi, Miwako; Shafer, Valerie L; Miyagawa, Shigeru; Kotek, Hadas; Sugawara, Ayaka; Pantazis, Dimitrios
2016-12-01
We examined discrimination of a second-language (L2) vowel duration contrast in English learners of Japanese (JP) with different amounts of experience using the magnetoencephalography mismatch field (MMF) component. Twelve L2 learners were tested before and after a second semester of college-level JP; half attended a regular rate course and half an accelerated course with more hours per week. Results showed no significant change in MMF for either the regular or accelerated learning group from beginning to end of the course. We also compared these groups against nine L2 learners who had completed four semesters of college-level JP. These 4-semester learners did not significantly differ from 2-semester learners, in that only a difference in hemisphere activation (interacting with time) between the two groups approached significance. These findings suggest that targeted training of L2 phonology may be necessary to allow for changes in processing of L2 speech contrasts at an early, automatic level. Copyright © 2016 Elsevier B.V. All rights reserved.
Estimating psycho-physiological state of a human by speech analysis
NASA Astrophysics Data System (ADS)
Ronzhin, A. L.
2005-05-01
Adverse effects of intoxication, fatigue and boredom could degrade performance of highly trained operators of complex technical systems with potentially catastrophic consequences. Existing physiological fitness for duty tests are time consuming, costly, invasive, and highly unpopular. Known non-physiological tests constitute a secondary task and interfere with the busy workload of the tested operator. Various attempts to assess the current status of the operator by processing of "normal operational data" often lead to excessive amount of computations, poorly justified metrics, and ambiguity of results. At the same time, speech analysis presents a natural, non-invasive approach based upon well-established efficient data processing. In addition, it supports both behavioral and physiological biometric. This paper presents an approach facilitating robust speech analysis/understanding process in spite of natural speech variability and background noise. Automatic speech recognition is suggested as a technique for the detection of changes in the psycho-physiological state of a human that typically manifest themselves by changes of characteristics of voice tract and semantic-syntactic connectivity of conversation. Preliminary tests have confirmed that the statistically significant correlation between the error rate of automatic speech recognition and the extent of alcohol intoxication does exist. In addition, the obtained data allowed exploring some interesting correlations and establishing some quantitative models. It is proposed to utilize this approach as a part of fitness for duty test and compare its efficiency with analyses of iris, face geometry, thermography and other popular non-invasive biometric techniques.
Relationship between listeners' nonnative speech recognition and categorization abilities
Atagi, Eriko; Bent, Tessa
2015-01-01
Enhancement of the perceptual encoding of talker characteristics (indexical information) in speech can facilitate listeners' recognition of linguistic content. The present study explored this indexical-linguistic relationship in nonnative speech processing by examining listeners' performance on two tasks: nonnative accent categorization and nonnative speech-in-noise recognition. Results indicated substantial variability across listeners in their performance on both the accent categorization and nonnative speech recognition tasks. Moreover, listeners' accent categorization performance correlated with their nonnative speech-in-noise recognition performance. These results suggest that having more robust indexical representations for nonnative accents may allow listeners to more accurately recognize the linguistic content of nonnative speech. PMID:25618098
Research in speech communication.
Flanagan, J
1995-10-24
Advances in digital speech processing are now supporting application and deployment of a variety of speech technologies for human/machine communication. In fact, new businesses are rapidly forming about these technologies. But these capabilities are of little use unless society can afford them. Happily, explosive advances in microelectronics over the past two decades have assured affordable access to this sophistication as well as to the underlying computing technology. The research challenges in speech processing remain in the traditionally identified areas of recognition, synthesis, and coding. These three areas have typically been addressed individually, often with significant isolation among the efforts. But they are all facets of the same fundamental issue--how to represent and quantify the information in the speech signal. This implies deeper understanding of the physics of speech production, the constraints that the conventions of language impose, and the mechanism for information processing in the auditory system. In ongoing research, therefore, we seek more accurate models of speech generation, better computational formulations of language, and realistic perceptual guides for speech processing--along with ways to coalesce the fundamental issues of recognition, synthesis, and coding. Successful solution will yield the long-sought dictation machine, high-quality synthesis from text, and the ultimate in low bit-rate transmission of speech. It will also open the door to language-translating telephony, where the synthetic foreign translation can be in the voice of the originating talker.
Searchfield, Grant D; Linford, Tania; Kobayashi, Kei; Crowhen, David; Latzel, Matthias
2018-03-01
To compare preference for and performance of manually selected programmes to an automatic sound classifier, the Phonak AutoSense OS. A single blind repeated measures study. Participants were fit with Phonak Virto V90 ITE aids; preferences for different listening programmes were compared across four different sound scenarios (speech in: quiet, noise, loud noise and a car). Following a 4-week trial preferences were reassessed and the users preferred programme was compared to the automatic classifier for sound quality and hearing in noise (HINT test) using a 12 loudspeaker array. Twenty-five participants with symmetrical moderate-severe sensorineural hearing loss. Participant preferences of manual programme for scenarios varied considerably between and within sessions. A HINT Speech Reception Threshold (SRT) advantage was observed for the automatic classifier over participant's manual selection for speech in quiet, loud noise and car noise. Sound quality ratings were similar for both manual and automatic selections. The use of a sound classifier is a viable alternative to manual programme selection.
Zekveld, Adriana A.; Kramer, Sophia E.; Kessens, Judith M.; Vlaming, Marcel S. M. G.; Houtgast, Tammo
2009-01-01
This study examined the subjective benefit obtained from automatically generated captions during telephone-speech comprehension in the presence of babble noise. Short stories were presented by telephone either with or without captions that were generated offline by an automatic speech recognition (ASR) system. To simulate online ASR, the word accuracy (WA) level of the captions was 60% or 70% and the text was presented delayed to the speech. After each test, the hearing impaired participants (n = 20) completed the NASA-Task Load Index and several rating scales evaluating the support from the captions. Participants indicated that using the erroneous text in speech comprehension was difficult and the reported task load did not differ between the audio + text and audio-only conditions. In a follow-up experiment (n = 10), the perceived benefit of presenting captions increased with an increase of WA levels to 80% and 90%, and elimination of the text delay. However, in general, the task load did not decrease when captions were presented. These results suggest that the extra effort required to process the text could have been compensated for by less effort required to comprehend the speech. Future research should aim at reducing the complexity of the task to increase the willingness of hearing impaired persons to use an assistive communication system automatically providing captions. The current results underline the need for obtaining both objective and subjective measures of benefit when evaluating assistive communication systems. PMID:19126551
An Acquired Deficit of Audiovisual Speech Processing
ERIC Educational Resources Information Center
Hamilton, Roy H.; Shenton, Jeffrey T.; Coslett, H. Branch
2006-01-01
We report a 53-year-old patient (AWF) who has an acquired deficit of audiovisual speech integration, characterized by a perceived temporal mismatch between speech sounds and the sight of moving lips. AWF was less accurate on an auditory digit span task with vision of a speaker's face as compared to a condition in which no visual information from…
Development and Perceptual Evaluation of Amplitude-Based F0 Control in Electrolarynx Speech
ERIC Educational Resources Information Center
Saikachi, Yoko; Stevens, Kenneth N.; Hillman, Robert E.
2009-01-01
Purpose: Current electrolarynx (EL) devices produce a mechanical speech quality that has been largely attributed to the lack of natural fundamental frequency (F0) variation. In order to improve the quality of EL speech, in the present study the authors aimed to develop and evaluate an automatic F0 control scheme, in which F0 was modulated based on…
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.
Cortical activity patterns predict robust speech discrimination ability in noise
Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.
2012-01-01
The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331
Human phoneme recognition depending on speech-intrinsic variability.
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).
Automatic measurement of prosody in behavioral variant FTD.
Nevler, Naomi; Ash, Sharon; Jester, Charles; Irwin, David J; Liberman, Mark; Grossman, Murray
2017-08-15
To help understand speech changes in behavioral variant frontotemporal dementia (bvFTD), we developed and implemented automatic methods of speech analysis for quantification of prosody, and evaluated clinical and anatomical correlations. We analyzed semi-structured, digitized speech samples from 32 patients with bvFTD (21 male, mean age 63 ± 8.5, mean disease duration 4 ± 3.1 years) and 17 matched healthy controls (HC). We automatically extracted fundamental frequency (f0, the physical property of sound most closely correlating with perceived pitch) and computed pitch range on a logarithmic scale (semitone) that controls for individual and sex differences. We correlated f0 range with neuropsychiatric tests, and related f0 range to gray matter (GM) atrophy using 3T T1 MRI. We found significantly reduced f0 range in patients with bvFTD (mean 4.3 ± 1.8 ST) compared to HC (5.8 ± 2.1 ST; p = 0.03). Regression related reduced f0 range in bvFTD to GM atrophy in bilateral inferior and dorsomedial frontal as well as left anterior cingulate and anterior insular regions. Reduced f0 range reflects impaired prosody in bvFTD. This is associated with neuroanatomic networks implicated in language production and social disorders centered in the frontal lobe. These findings support the feasibility of automated speech analysis in frontotemporal dementia and other disorders. © 2017 American Academy of Neurology.
The Mechanical Recognition of Speech: Prospects for Use in the Teaching of Languages.
ERIC Educational Resources Information Center
Pulliam, Robert
1970-01-01
This paper begins with a brief account of the development of automatic speech recogniton (ASR) and then proceeds to an examination of ASR systems typical of the kind now in operation. It is stressed that such systems, although highly developed, do not recognize speech in the same sense as the human being does, and that they can not deal with a…
Research in speech communication.
Flanagan, J
1995-01-01
Advances in digital speech processing are now supporting application and deployment of a variety of speech technologies for human/machine communication. In fact, new businesses are rapidly forming about these technologies. But these capabilities are of little use unless society can afford them. Happily, explosive advances in microelectronics over the past two decades have assured affordable access to this sophistication as well as to the underlying computing technology. The research challenges in speech processing remain in the traditionally identified areas of recognition, synthesis, and coding. These three areas have typically been addressed individually, often with significant isolation among the efforts. But they are all facets of the same fundamental issue--how to represent and quantify the information in the speech signal. This implies deeper understanding of the physics of speech production, the constraints that the conventions of language impose, and the mechanism for information processing in the auditory system. In ongoing research, therefore, we seek more accurate models of speech generation, better computational formulations of language, and realistic perceptual guides for speech processing--along with ways to coalesce the fundamental issues of recognition, synthesis, and coding. Successful solution will yield the long-sought dictation machine, high-quality synthesis from text, and the ultimate in low bit-rate transmission of speech. It will also open the door to language-translating telephony, where the synthetic foreign translation can be in the voice of the originating talker. Images Fig. 1 Fig. 2 Fig. 5 Fig. 8 Fig. 11 Fig. 12 Fig. 13 PMID:7479806
Watkins, Greg D; Swanson, Brett A; Suaning, Gregg J
2018-02-22
sentences used an adaptive procedure, with the speech presented at a fixed level and the ISNR varied. In data set 2, sentences were presented at 65 dB SPL in the presence of stationary speech weighted noise, street-side city noise, and cocktail party noise. An adaptive ISNR procedure was used. In data set 3, sentences were presented at levels ranging from 55 to 89 dB SPL with two automatic gain control configurations and two fixed ISNRs. For data set 1, the ISNR and OSNR were equally most accurate. STOI was significantly different for deviance (p = 0.045) and RMSE* (p < 0.001). VSTOI was significantly different for RMSE* (p < 0.001). For data set 2, ISNR and OSNR had an equivalent accuracy which was significantly better than that of STOI for PSIG (p = 0.029) and VSTOI for deviance (p = 0.001), RMSE*, and PSIG (both p < 0.001). For data set 3, OSNR was the most accurate metric and was significantly more accurate than VSTOI for deviance, RMSE*, and PSIG (all p < 0.001). ISNR and STOI were unable to predict the sentence scores for this data set. The study results supported the hypotheses. OSNR was found to have an accuracy equivalent to or better than ISNR, STOI, and VSTOI for tests conducted at a fixed presentation level and variable ISNR. OSNR was a more accurate metric than VSTOI for tests with fixed ISNRs and variable presentation levels. Overall, OSNR was the most accurate metric across the three data sets. OSNR holds promise as a prediction metric which could potentially improve the effectiveness of sound processor research and CI fitting.
A social feedback loop for speech development and its reduction in autism
Warlaumont, Anne S.; Richards, Jeffrey A.; Gilkerson, Jill; Oller, D. Kimbrough
2014-01-01
We analyze the microstructure of child-adult interaction during naturalistic, daylong, automatically labeled audio recordings (13,836 hours total) of children (8- to 48-month-olds) with and without autism. We find that adult responses are more likely when child vocalizations are speech-related. In turn, a child vocalization is more likely to be speech-related if the previous speech-related child vocalization received an immediate adult response. Taken together, these results are consistent with the idea that there is a social feedback loop between child and caregiver that promotes speech-language development. Although this feedback loop applies in both typical development and autism, children with autism produce proportionally fewer speech-related vocalizations and the responses they receive are less contingent on whether their vocalizations are speech-related. We argue that such differences will diminish the strength of the social feedback loop with cascading effects on speech development over time. Differences related to socioeconomic status are also reported. PMID:24840717
Stochastic Modeling as a Means of Automatic Speech Recognition
1975-04-01
companng ihc features of different speech recognition systems, attention is often focused on thc control structures and the methods o’ communication...with no need to use secondary storage . Note that we go from a group of separate knowledge sources to an integrated network representation in...exhaust the available lime or storage . - - - . . 1- .-.-.. mmm^~ i — ■ ■ ’ ■ C haplcr I - IN I ROÜliCl ION Page 13 On the other hand
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
NASA Astrophysics Data System (ADS)
Kardava, Irakli; Tadyszak, Krzysztof; Gulua, Nana; Jurga, Stefan
2017-02-01
For more flexibility of environmental perception by artificial intelligence it is needed to exist the supporting software modules, which will be able to automate the creation of specific language syntax and to make a further analysis for relevant decisions based on semantic functions. According of our proposed approach, of which implementation it is possible to create the couples of formal rules of given sentences (in case of natural languages) or statements (in case of special languages) by helping of computer vision, speech recognition or editable text conversion system for further automatic improvement. In other words, we have developed an approach, by which it can be achieved to significantly improve the training process automation of artificial intelligence, which as a result will give us a higher level of self-developing skills independently from us (from users). At the base of our approach we have developed a software demo version, which includes the algorithm and software code for the entire above mentioned component's implementation (computer vision, speech recognition and editable text conversion system). The program has the ability to work in a multi - stream mode and simultaneously create a syntax based on receiving information from several sources.
Bentsen, Thomas; May, Tobias; Kressner, Abigail A; Dau, Torsten
2018-01-01
Computational speech segregation attempts to automatically separate speech from noise. This is challenging in conditions with interfering talkers and low signal-to-noise ratios. Recent approaches have adopted deep neural networks and successfully demonstrated speech intelligibility improvements. A selection of components may be responsible for the success with these state-of-the-art approaches: the system architecture, a time frame concatenation technique and the learning objective. The aim of this study was to explore the roles and the relative contributions of these components by measuring speech intelligibility in normal-hearing listeners. A substantial improvement of 25.4 percentage points in speech intelligibility scores was found going from a subband-based architecture, in which a Gaussian Mixture Model-based classifier predicts the distributions of speech and noise for each frequency channel, to a state-of-the-art deep neural network-based architecture. Another improvement of 13.9 percentage points was obtained by changing the learning objective from the ideal binary mask, in which individual time-frequency units are labeled as either speech- or noise-dominated, to the ideal ratio mask, where the units are assigned a continuous value between zero and one. Therefore, both components play significant roles and by combining them, speech intelligibility improvements were obtained in a six-talker condition at a low signal-to-noise ratio.
Moharir, Madhavi; Barnett, Noel; Taras, Jillian; Cole, Martha; Ford-Jones, E Lee; Levin, Leo
2014-01-01
Failure to recognize and intervene early in speech and language delays can lead to multifaceted and potentially severe consequences for early child development and later literacy skills. While routine evaluations of speech and language during well-child visits are recommended, there is no standardized (office) approach to facilitate this. Furthermore, extensive wait times for speech and language pathology consultation represent valuable lost time for the child and family. Using speech and language expertise, and paediatric collaboration, key content for an office-based tool was developed. early and accurate identification of speech and language delays as well as children at risk for literacy challenges; appropriate referral to speech and language services when required; and teaching and, thus, empowering parents to create rich and responsive language environments at home. Using this tool, in combination with the Canadian Paediatric Society's Read, Speak, Sing and Grow Literacy Initiative, physicians will be better positioned to offer practical strategies to caregivers to enhance children's speech and language capabilities. The tool represents a strategy to evaluate speech and language delays. It depicts age-specific linguistic/phonetic milestones and suggests interventions. The tool represents a practical interim treatment while the family is waiting for formal speech and language therapy consultation.
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.
Speech training alters tone frequency tuning in rat primary auditory cortex
Engineer, Crystal T.; Perez, Claudia A.; Carraway, Ryan S.; Chang, Kevin Q.; Roland, Jarod L.; Kilgard, Michael P.
2013-01-01
Previous studies in both humans and animals have documented improved performance following discrimination training. This enhanced performance is often associated with cortical response changes. In this study, we tested the hypothesis that long-term speech training on multiple tasks can improve primary auditory cortex (A1) responses compared to rats trained on a single speech discrimination task or experimentally naïve rats. Specifically, we compared the percent of A1 responding to trained sounds, the responses to both trained and untrained sounds, receptive field properties of A1 neurons, and the neural discrimination of pairs of speech sounds in speech trained and naïve rats. Speech training led to accurate discrimination of consonant and vowel sounds, but did not enhance A1 response strength or the neural discrimination of these sounds. Speech training altered tone responses in rats trained on six speech discrimination tasks but not in rats trained on a single speech discrimination task. Extensive speech training resulted in broader frequency tuning, shorter onset latencies, a decreased driven response to tones, and caused a shift in the frequency map to favor tones in the range where speech sounds are the loudest. Both the number of trained tasks and the number of days of training strongly predict the percent of A1 responding to a low frequency tone. Rats trained on a single speech discrimination task performed less accurately than rats trained on multiple tasks and did not exhibit A1 response changes. Our results indicate that extensive speech training can reorganize the A1 frequency map, which may have downstream consequences on speech sound processing. PMID:24344364
A social feedback loop for speech development and its reduction in autism.
Warlaumont, Anne S; Richards, Jeffrey A; Gilkerson, Jill; Oller, D Kimbrough
2014-07-01
We analyzed the microstructure of child-adult interaction during naturalistic, daylong, automatically labeled audio recordings (13,836 hr total) of children (8- to 48-month-olds) with and without autism. We found that an adult was more likely to respond when the child's vocalization was speech related rather than not speech related. In turn, a child's vocalization was more likely to be speech related if the child's previous speech-related vocalization had received an immediate adult response rather than no response. Taken together, these results are consistent with the idea that there is a social feedback loop between child and caregiver that promotes speech development. Although this feedback loop applies in both typical development and autism, children with autism produced proportionally fewer speech-related vocalizations, and the responses they received were less contingent on whether their vocalizations were speech related. We argue that such differences will diminish the strength of the social feedback loop and have cascading effects on speech development over time. Differences related to socioeconomic status are also reported. © The Author(s) 2014.
Study of acoustic correlates associate with emotional speech
NASA Astrophysics Data System (ADS)
Yildirim, Serdar; Lee, Sungbok; Lee, Chul Min; Bulut, Murtaza; Busso, Carlos; Kazemzadeh, Ebrahim; Narayanan, Shrikanth
2004-10-01
This study investigates the acoustic characteristics of four different emotions expressed in speech. The aim is to obtain detailed acoustic knowledge on how a speech signal is modulated by changes from neutral to a certain emotional state. Such knowledge is necessary for automatic emotion recognition and classification and emotional speech synthesis. Speech data obtained from two semi-professional actresses are analyzed and compared. Each subject produces 211 sentences with four different emotions; neutral, sad, angry, happy. We analyze changes in temporal and acoustic parameters such as magnitude and variability of segmental duration, fundamental frequency and the first three formant frequencies as a function of emotion. Acoustic differences among the emotions are also explored with mutual information computation, multidimensional scaling and acoustic likelihood comparison with normal speech. Results indicate that speech associated with anger and happiness is characterized by longer duration, shorter interword silence, higher pitch and rms energy with wider ranges. Sadness is distinguished from other emotions by lower rms energy and longer interword silence. Interestingly, the difference in formant pattern between [happiness/anger] and [neutral/sadness] are better reflected in back vowels such as /a/(/father/) than in front vowels. Detailed results on intra- and interspeaker variability will be reported.
Common cues to emotion in the dynamic facial expressions of speech and song.
Livingstone, Steven R; Thompson, William F; Wanderley, Marcelo M; Palmer, Caroline
2015-01-01
Speech and song are universal forms of vocalization that may share aspects of emotional expression. Research has focused on parallels in acoustic features, overlooking facial cues to emotion. In three experiments, we compared moving facial expressions in speech and song. In Experiment 1, vocalists spoke and sang statements each with five emotions. Vocalists exhibited emotion-dependent movements of the eyebrows and lip corners that transcended speech-song differences. Vocalists' jaw movements were coupled to their acoustic intensity, exhibiting differences across emotion and speech-song. Vocalists' emotional movements extended beyond vocal sound to include large sustained expressions, suggesting a communicative function. In Experiment 2, viewers judged silent videos of vocalists' facial expressions prior to, during, and following vocalization. Emotional intentions were identified accurately for movements during and after vocalization, suggesting that these movements support the acoustic message. Experiment 3 compared emotional identification in voice-only, face-only, and face-and-voice recordings. Emotion judgements for voice-only singing were poorly identified, yet were accurate for all other conditions, confirming that facial expressions conveyed emotion more accurately than the voice in song, yet were equivalent in speech. Collectively, these findings highlight broad commonalities in the facial cues to emotion in speech and song, yet highlight differences in perception and acoustic-motor production.
The influence of ambient speech on adult speech productions through unintentional imitation.
Delvaux, Véronique; Soquet, Alain
2007-01-01
This paper deals with the influence of ambient speech on individual speech productions. A methodological framework is defined to gather the experimental data necessary to feed computer models simulating self-organisation in phonological systems. Two experiments were carried out. Experiment 1 was run on French native speakers from two regiolects of Belgium: two from Liège and two from Brussels. When exposed to the way of speaking of the other regiolect via loudspeakers, the speakers of one regiolect produced vowels that were significantly different from their typical realisations, and significantly closer to the way of speaking specific of the other regiolect. Experiment 2 achieved a replication of the results for 8 Mons speakers hearing a Liège speaker. A significant part of the imitative effect remained up to 10 min after the end of the exposure to the other regiolect productions. As a whole, the results suggest that: (i) imitation occurs automatically and unintentionally, (ii) the modified realisations leave a memory trace, in which case the mechanism may be better defined as 'mimesis' than as 'imitation'. The potential effects of multiple imitative speech interactions on sound change are discussed in this paper, as well as the implications for a general theory of phonetic implementation and phonetic representation.
Effects and modeling of phonetic and acoustic confusions in accented speech.
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.
Oral Articulatory Control in Childhood Apraxia of Speech
Moss, Aviva; Lu, Ying
2015-01-01
Purpose The purpose of this research was to examine spatial and temporal aspects of articulatory control in children with childhood apraxia of speech (CAS), children with speech delay characterized by an articulation/phonological impairment (SD), and controls with typical development (TD) during speech tasks that increased in word length. Method The participants included 33 children (11 CAS, 11 SD, and 11 TD) between 3 and 7 years of age. A motion capture system was used to track jaw, lower lip, and upper lip movement during a naming task. Movement duration, velocity, displacement, and variability were measured from accurate word productions. Results Movement variability was significantly higher in the children with CAS compared with participants in the SD and TD groups. Differences in temporal control were seen between both groups of children with speech impairment and the controls with TD during accurate word productions. As word length increased, movement duration and variability differed between the children with CAS and those with SD. Conclusions These findings provide evidence that movement variability distinguishes children with CAS from speakers with SD. Kinematic differences between the participants with CAS and those with SD suggest that these groups respond differently to linguistic challenges. PMID:25951237
Moharir, Madhavi; Barnett, Noel; Taras, Jillian; Cole, Martha; Ford-Jones, E Lee; Levin, Leo
2014-01-01
Failure to recognize and intervene early in speech and language delays can lead to multifaceted and potentially severe consequences for early child development and later literacy skills. While routine evaluations of speech and language during well-child visits are recommended, there is no standardized (office) approach to facilitate this. Furthermore, extensive wait times for speech and language pathology consultation represent valuable lost time for the child and family. Using speech and language expertise, and paediatric collaboration, key content for an office-based tool was developed. The tool aimed to help physicians achieve three main goals: early and accurate identification of speech and language delays as well as children at risk for literacy challenges; appropriate referral to speech and language services when required; and teaching and, thus, empowering parents to create rich and responsive language environments at home. Using this tool, in combination with the Canadian Paediatric Society’s Read, Speak, Sing and Grow Literacy Initiative, physicians will be better positioned to offer practical strategies to caregivers to enhance children’s speech and language capabilities. The tool represents a strategy to evaluate speech and language delays. It depicts age-specific linguistic/phonetic milestones and suggests interventions. The tool represents a practical interim treatment while the family is waiting for formal speech and language therapy consultation. PMID:24627648
ERIC Educational Resources Information Center
Hodge, Megan M.; Gotzke, Carrie L.
2011-01-01
Listeners' identification of young children's productions of minimally contrastive words and predictive relationships between accurately identified words and intelligibility scores obtained from a 100-word spontaneous speech sample were determined for 36 children with typically developing speech (TDS) and 36 children with speech sound disorders…
Automatic Online Lecture Highlighting Based on Multimedia Analysis
ERIC Educational Resources Information Center
Che, Xiaoyin; Yang, Haojin; Meinel, Christoph
2018-01-01
Textbook highlighting is widely considered to be beneficial for students. In this paper, we propose a comprehensive solution to highlight the online lecture videos in both sentence- and segment-level, just as is done with paper books. The solution is based on automatic analysis of multimedia lecture materials, such as speeches, transcripts, and…
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…
Federal Register 2010, 2011, 2012, 2013, 2014
2013-08-15
...] Speech-to-Speech and Internet Protocol (IP) Speech-to-Speech Telecommunications Relay Services...: This is a summary of the Commission's Speech-to-Speech and Internet Protocol (IP) Speech-to-Speech...), Internet Protocol Relay (IP Relay), and IP captioned telephone service (IP CTS) as compensable forms of TRS...
A new automatic blood pressure kit auscultates for accurate reading with a smartphone
Wu, Hongjun; Wang, Bingjian; Zhu, Xinpu; Chu, Guang; Zhang, Zhi
2016-01-01
Abstract The widely used oscillometric automated blood pressure (BP) monitor was continuously questioned on its accuracy. A novel BP kit named Accutension which adopted Korotkoff auscultation method was then devised. Accutension worked with a miniature microphone, a pressure sensor, and a smartphone. The BP values were automatically displayed on the smartphone screen through the installed App. Data recorded in the phone could be played back and reconfirmed after measurement. They could also be uploaded and saved to the iCloud. The accuracy and consistency of this novel electronic auscultatory sphygmomanometer was preliminarily verified here. Thirty-two subjects were included and 82 qualified readings were obtained. The mean differences ± SD for systolic and diastolic BP readings between Accutension and mercury sphygmomanometer were 0.87 ± 2.86 and −0.94 ± 2.93 mm Hg. Agreements between Accutension and mercury sphygmomanometer were highly significant for systolic (ICC = 0.993, 95% confidence interval (CI): 0.989–0.995) and diastolic (ICC = 0.987, 95% CI: 0.979–0.991). In conclusion, Accutension worked accurately based on our pilot study data. The difference was acceptable. ICC and Bland–Altman plot charts showed good agreements with manual measurements. Systolic readings of Accutension were slightly higher than those of manual measurement, while diastolic readings were slightly lower. One possible reason was that Accutension captured the first and the last korotkoff sound more sensitively than human ear during manual measurement and avoided sound missing, so that it might be more accurate than traditional mercury sphygmomanometer. By documenting and analyzing of variant tendency of BP values, Accutension helps management of hypertension and therefore contributes to the mobile heath service. PMID:27512876
On the Development of Speech Resources for the Mixtec Language
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
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…
Federal Register 2010, 2011, 2012, 2013, 2014
2013-08-15
...] Speech-to-Speech and Internet Protocol (IP) Speech-to-Speech Telecommunications Relay Services... Internet Protocol (IP) Speech-to-Speech Telecommunications Relay Services; Telecommunications Relay... (IP Relay) and video relay service (VRS), the Commission should bundle national STS outreach efforts...
Modular Neural Networks for Speech Recognition.
1996-08-01
automatic speech rccogni- tion, understanding and translation since the early 1950’ s . Although researchers have demonstrated impressive results with...nodes. It serves only as a data source for the following hidden layer( s ). Finally, the networks output is computed by neurons in the output layer. The...following update rule for weights in the hidden layer: w (,,•+I) ("’) E/V S (W W k- = wj, -- 7 - / v It is easy to generalize the backpropagation
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.
Joint Spatial-Spectral Feature Space Clustering for Speech Activity Detection from ECoG Signals
Kanas, Vasileios G.; Mporas, Iosif; Benz, Heather L.; Sgarbas, Kyriakos N.; Bezerianos, Anastasios; Crone, Nathan E.
2014-01-01
Brain machine interfaces for speech restoration have been extensively studied for more than two decades. The success of such a system will depend in part on selecting the best brain recording sites and signal features corresponding to speech production. The purpose of this study was to detect speech activity automatically from electrocorticographic signals based on joint spatial-frequency clustering of the ECoG feature space. For this study, the ECoG signals were recorded while a subject performed two different syllable repetition tasks. We found that the optimal frequency resolution to detect speech activity from ECoG signals was 8 Hz, achieving 98.8% accuracy by employing support vector machines (SVM) as a classifier. We also defined the cortical areas that held the most information about the discrimination of speech and non-speech time intervals. Additionally, the results shed light on the distinct cortical areas associated with the two syllable repetition tasks and may contribute to the development of portable ECoG-based communication. PMID:24658248
Vieira, Manuel; Fonseca, Paulo J; Amorim, M Clara P; Teixeira, Carlos J C
2015-12-01
The study of acoustic communication in animals often requires not only the recognition of species specific acoustic signals but also the identification of individual subjects, all in a complex acoustic background. Moreover, when very long recordings are to be analyzed, automatic recognition and identification processes are invaluable tools to extract the relevant biological information. A pattern recognition methodology based on hidden Markov models is presented inspired by successful results obtained in the most widely known and complex acoustical communication signal: human speech. This methodology was applied here for the first time to the detection and recognition of fish acoustic signals, specifically in a stream of round-the-clock recordings of Lusitanian toadfish (Halobatrachus didactylus) in their natural estuarine habitat. The results show that this methodology is able not only to detect the mating sounds (boatwhistles) but also to identify individual male toadfish, reaching an identification rate of ca. 95%. Moreover this method also proved to be a powerful tool to assess signal durations in large data sets. However, the system failed in recognizing other sound types.
Perceptual analysis of speech following traumatic brain injury in childhood.
Cahill, Louise M; Murdoch, Bruce E; Theodoros, Deborah G
2002-05-01
To investigate perceptually the speech dimensions, oromotor function, and speech intelligibility of a group of individuals with traumatic brain injury (TBI) acquired in childhood. The speech of 24 children with TBI was analysed perceptually and compared with that of a group of non-neurologically impaired children matched for age and sex. The 16 dysarthric TBI subjects were significantly less intelligible than the control subjects, and demonstrated significant impairment in 12 of the 33 speech dimensions rated. In addition, the eight non-dysarthric TBI subjects were significantly impaired in many areas of oromotor function on the Frenchay Dysarthria Assessment, indicating some degree of pre-clinical speech impairment. The results of the perceptual analysis are discussed in terms of the possible underlying pathophysiological bases of the deviant speech features identified, and the need for a comprehensive instrumental assessment, to more accurately determine the level of breakdown in the speech production mechanism in children following TBI.
Dual Key Speech Encryption Algorithm Based Underdetermined BSS
Zhao, Huan; Chen, Zuo; Zhang, Xixiang
2014-01-01
When the number of the mixed signals is less than that of the source signals, the underdetermined blind source separation (BSS) is a significant difficult problem. Due to the fact that the great amount data of speech communications and real-time communication has been required, we utilize the intractability of the underdetermined BSS problem to present a dual key speech encryption method. The original speech is mixed with dual key signals which consist of random key signals (one-time pad) generated by secret seed and chaotic signals generated from chaotic system. In the decryption process, approximate calculation is used to recover the original speech signals. The proposed algorithm for speech signals encryption can resist traditional attacks against the encryption system, and owing to approximate calculation, decryption becomes faster and more accurate. It is demonstrated that the proposed method has high level of security and can recover the original signals quickly and efficiently yet maintaining excellent audio quality. PMID:24955430
Automatic transducer switching provides accurate wide range measurement of pressure differential
NASA Technical Reports Server (NTRS)
Yoder, S. K.
1967-01-01
Automatic pressure transducer switching network sequentially selects any one of a number of limited-range transducers as gas pressure rises or falls, extending the range of measurement and lessening the chances of damage due to high pressure.
Effect of Dialect on the Identification of Speech Impairment in Indigenous Children
ERIC Educational Resources Information Center
Laffey, Kate; Pearce, Wendy M.; Steed, William
2014-01-01
The influence of dialect on child speech assessment processes is important to consider in order to ensure accurate diagnosis and appropriate intervention (teaching or therapy) for bidialectal children. In Australia, there is limited research evidence documenting the influence of dialectal variations on identification of speech impairment among…
Ali, Zulfiqar; Alsulaiman, Mansour; Muhammad, Ghulam; Elamvazuthi, Irraivan; Al-Nasheri, Ahmed; Mesallam, Tamer A; Farahat, Mohamed; Malki, Khalid H
2017-05-01
A large population around the world has voice complications. Various approaches for subjective and objective evaluations have been suggested in the literature. The subjective approach strongly depends on the experience and area of expertise of a clinician, and human error cannot be neglected. On the other hand, the objective or automatic approach is noninvasive. Automatic developed systems can provide complementary information that may be helpful for a clinician in the early screening of a voice disorder. At the same time, automatic systems can be deployed in remote areas where a general practitioner can use them and may refer the patient to a specialist to avoid complications that may be life threatening. Many automatic systems for disorder detection have been developed by applying different types of conventional speech features such as the linear prediction coefficients, linear prediction cepstral coefficients, and Mel-frequency cepstral coefficients (MFCCs). This study aims to ascertain whether conventional speech features detect voice pathology reliably, and whether they can be correlated with voice quality. To investigate this, an automatic detection system based on MFCC was developed, and three different voice disorder databases were used in this study. The experimental results suggest that the accuracy of the MFCC-based system varies from database to database. The detection rate for the intra-database ranges from 72% to 95%, and that for the inter-database is from 47% to 82%. The results conclude that conventional speech features are not correlated with voice, and hence are not reliable in pathology detection. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.
Effects of low harmonics on tone identification in natural and vocoded speech.
Liu, Chang; Azimi, Behnam; Tahmina, Qudsia; Hu, Yi
2012-11-01
This study investigated the contribution of low-frequency harmonics to identifying Mandarin tones in natural and vocoded speech in quiet and noisy conditions. Results showed that low-frequency harmonics of natural speech led to highly accurate tone identification; however, for vocoded speech, low-frequency harmonics yielded lower tone identification than stimuli with full harmonics, except for tone 4. Analysis of the correlation between tone accuracy and the amplitude-F0 correlation index suggested that "more" speech contents (i.e., more harmonics) did not necessarily yield better tone recognition for vocoded speech, especially when the amplitude contour of the signals did not co-vary with the F0 contour.
Rusz, J; Cmejla, R; Ruzickova, H; Ruzicka, E
2011-01-01
An assessment of vocal impairment is presented for separating healthy people from persons with early untreated Parkinson's disease (PD). This study's main purpose was to (a) determine whether voice and speech disorder are present from early stages of PD before starting dopaminergic pharmacotherapy, (b) ascertain the specific characteristics of the PD-related vocal impairment, (c) identify PD-related acoustic signatures for the major part of traditional clinically used measurement methods with respect to their automatic assessment, and (d) design new automatic measurement methods of articulation. The varied speech data were collected from 46 Czech native speakers, 23 with PD. Subsequently, 19 representative measurements were pre-selected, and Wald sequential analysis was then applied to assess the efficiency of each measure and the extent of vocal impairment of each subject. It was found that measurement of the fundamental frequency variations applied to two selected tasks was the best method for separating healthy from PD subjects. On the basis of objective acoustic measures, statistical decision-making theory, and validation from practicing speech therapists, it has been demonstrated that 78% of early untreated PD subjects indicate some form of vocal impairment. The speech defects thus uncovered differ individually in various characteristics including phonation, articulation, and prosody.
Exploring expressivity and emotion with artificial voice and speech technologies.
Pauletto, Sandra; Balentine, Bruce; Pidcock, Chris; Jones, Kevin; Bottaci, Leonardo; Aretoulaki, Maria; Wells, Jez; Mundy, Darren P; Balentine, James
2013-10-01
Emotion in audio-voice signals, as synthesized by text-to-speech (TTS) technologies, was investigated to formulate a theory of expression for user interface design. Emotional parameters were specified with markup tags, and the resulting audio was further modulated with post-processing techniques. Software was then developed to link a selected TTS synthesizer with an automatic speech recognition (ASR) engine, producing a chatbot that could speak and listen. Using these two artificial voice subsystems, investigators explored both artistic and psychological implications of artificial speech emotion. Goals of the investigation were interdisciplinary, with interest in musical composition, augmentative and alternative communication (AAC), commercial voice announcement applications, human-computer interaction (HCI), and artificial intelligence (AI). The work-in-progress points towards an emerging interdisciplinary ontology for artificial voices. As one study output, HCI tools are proposed for future collaboration.
Abnormal laughter-like vocalisations replacing speech in primary progressive aphasia.
Rohrer, Jonathan D; Warren, Jason D; Rossor, Martin N
2009-09-15
We describe ten patients with a clinical diagnosis of primary progressive aphasia (PPA) (pathologically confirmed in three cases) who developed abnormal laughter-like vocalisations in the context of progressive speech output impairment leading to mutism. Failure of speech output was accompanied by increasing frequency of the abnormal vocalisations until ultimately they constituted the patient's only extended utterance. The laughter-like vocalisations did not show contextual sensitivity but occurred as an automatic vocal output that replaced speech. Acoustic analysis of the vocalisations in two patients revealed abnormal motor features including variable note duration and inter-note interval, loss of temporal symmetry of laugh notes and loss of the normal decrescendo. Abnormal laughter-like vocalisations may be a hallmark of a subgroup in the PPA spectrum with impaired control and production of nonverbal vocal behaviour due to disruption of fronto-temporal networks mediating vocalisation.
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.
Speech input system for meat inspection and pathological coding used thereby
NASA Astrophysics Data System (ADS)
Abe, Shozo
Meat inspection is one of exclusive and important jobs of veterinarians though it is not well known in general. As the inspection should be conducted skillfully during a series of continuous operations in a slaughter house, development of automatic inspecting systems has been required for a long time. We employed a hand-free speech input system to record the inspecting data because inspecters have to use their both hands to treat the internals of catles and check their health conditions by necked eyes. The data collected by the inspectors are transfered to a speech recognizer and then stored as controlable data of each catle inspected. Control of terms such as pathological conditions to be input and their coding are also important in this speech input system and practical examples are shown.
Kouider, Sid; Dupoux, Emmanuel
2005-08-01
We present a novel subliminal priming technique that operates in the auditory modality. Masking is achieved by hiding a spoken word within a stream of time-compressed speechlike sounds with similar spectral characteristics. Participants were unable to consciously identify the hidden words, yet reliable repetition priming was found. This effect was unaffected by a change in the speaker's voice and remained restricted to lexical processing. The results show that the speech modality, like the written modality, involves the automatic extraction of abstract word-form representations that do not include nonlinguistic details. In both cases, priming operates at the level of discrete and abstract lexical entries and is little influenced by overlap in form or semantics.
Learning diagnostic models using speech and language measures.
Peintner, Bart; Jarrold, William; Vergyriy, Dimitra; Richey, Colleen; Tempini, Maria Luisa Gorno; Ogar, Jennifer
2008-01-01
We describe results that show the effectiveness of machine learning in the automatic diagnosis of certain neurodegenerative diseases, several of which alter speech and language production. We analyzed audio from 9 control subjects and 30 patients diagnosed with one of three subtypes of Frontotemporal Lobar Degeneration. From this data, we extracted features of the audio signal and the words the patient used, which were obtained using our automated transcription technologies. We then automatically learned models that predict the diagnosis of the patient using these features. Our results show that learned models over these features predict diagnosis with accuracy significantly better than random. Future studies using higher quality recordings will likely improve these results.
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.
Improving Understanding of Emotional Speech Acoustic Content
NASA Astrophysics Data System (ADS)
Tinnemore, Anna
Children with cochlear implants show deficits in identifying emotional intent of utterances without facial or body language cues. A known limitation to cochlear implants is the inability to accurately portray the fundamental frequency contour of speech which carries the majority of information needed to identify emotional intent. Without reliable access to the fundamental frequency, other methods of identifying vocal emotion, if identifiable, could be used to guide therapies for training children with cochlear implants to better identify vocal emotion. The current study analyzed recordings of adults speaking neutral sentences with a set array of emotions in a child-directed and adult-directed manner. The goal was to identify acoustic cues that contribute to emotion identification that may be enhanced in child-directed speech, but are also present in adult-directed speech. Results of this study showed that there were significant differences in the variation of the fundamental frequency, the variation of intensity, and the rate of speech among emotions and between intended audiences.
Text-to-audiovisual speech synthesizer for children with learning disabilities.
Mendi, Engin; Bayrak, Coskun
2013-01-01
Learning disabilities affect the ability of children to learn, despite their having normal intelligence. Assistive tools can highly increase functional capabilities of children with learning disorders such as writing, reading, or listening. In this article, we describe a text-to-audiovisual synthesizer that can serve as an assistive tool for such children. The system automatically converts an input text to audiovisual speech, providing synchronization of the head, eye, and lip movements of the three-dimensional face model with appropriate facial expressions and word flow of the text. The proposed system can enhance speech perception and help children having learning deficits to improve their chances of success.
An automatic speech recognition system with speaker-independent identification support
NASA Astrophysics Data System (ADS)
Caranica, Alexandru; Burileanu, Corneliu
2015-02-01
The novelty of this work relies on the application of an open source research software toolkit (CMU Sphinx) to train, build and evaluate a speech recognition system, with speaker-independent support, for voice-controlled hardware applications. Moreover, we propose to use the trained acoustic model to successfully decode offline voice commands on embedded hardware, such as an ARMv6 low-cost SoC, Raspberry PI. This type of single-board computer, mainly used for educational and research activities, can serve as a proof-of-concept software and hardware stack for low cost voice automation systems.
LANDMARK-BASED SPEECH RECOGNITION: REPORT OF THE 2004 JOHNS HOPKINS SUMMER WORKSHOP.
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.
Lauritzen, Ted
1982-01-01
A measuring system is disclosed for surveying and very accurately positioning objects with respect to a reference line. A principal use of this surveying system is for accurately aligning the electromagnets which direct a particle beam emitted from a particle accelerator. Prior art surveying systems require highly skilled surveyors. Prior art systems include, for example, optical surveying systems which are susceptible to operator reading errors, and celestial navigation-type surveying systems, with their inherent complexities. The present invention provides an automatic readout micrometer which can very accurately measure distances. The invention has a simplicity of operation which practically eliminates the possibilities of operator optical reading error, owning to the elimination of traditional optical alignments for making measurements. The invention has an extendable arm which carries a laser surveying target. The extendable arm can be continuously positioned over its entire length of travel by either a coarse or fine adjustment without having the fine adjustment outrun the coarse adjustment until a reference laser beam is centered on the target as indicated by a digital readout. The length of the micrometer can then be accurately and automatically read by a computer and compared with a standardized set of alignment measurements. Due to its construction, the micrometer eliminates any errors due to temperature changes when the system is operated within a standard operating temperature range.
Lauritzen, T.
A measuring system is described for surveying and very accurately positioning objects with respect to a reference line. A principle use of this surveying system is for accurately aligning the electromagnets which direct a particle beam emitted from a particle accelerator. Prior art surveying systems require highly skilled surveyors. Prior art systems include, for example, optical surveying systems which are susceptible to operator reading errors, and celestial navigation-type surveying systems, with their inherent complexities. The present invention provides an automatic readout micrometer which can very accurately measure distances. The invention has a simplicity of operation which practically eliminates the possibilities of operator optical reading error, owning to the elimination of traditional optical alignments for making measurements. The invention has an extendable arm which carries a laser surveying target. The extendable arm can be continuously positioned over its entire length of travel by either a coarse of fine adjustment without having the fine adjustment outrun the coarse adjustment until a reference laser beam is centered on the target as indicated by a digital readout. The length of the micrometer can then be accurately and automatically read by a computer and compared with a standardized set of alignment measurements. Due to its construction, the micrometer eliminates any errors due to temperature changes when the system is operated within a standard operating temperature range.
Speech enhancement based on modified phase-opponency detectors
NASA Astrophysics Data System (ADS)
Deshmukh, Om D.; Espy-Wilson, Carol Y.
2005-09-01
A speech enhancement algorithm based on a neural model was presented by Deshmukh et al., [149th meeting of the Acoustical Society America, 2005]. The algorithm consists of a bank of Modified Phase Opponency (MPO) filter pairs tuned to different center frequencies. This algorithm is able to enhance salient spectral features in speech signals even at low signal-to-noise ratios. However, the algorithm introduces musical noise and sometimes misses a spectral peak that is close in frequency to a stronger spectral peak. Refinement in the design of the MPO filters was recently made that takes advantage of the falling spectrum of the speech signal in sonorant regions. The modified set of filters leads to better separation of the noise and speech signals, and more accurate enhancement of spectral peaks. The improvements also lead to a significant reduction in musical noise. Continuity algorithms based on the properties of speech signals are used to further reduce the musical noise effect. The efficiency of the proposed method in enhancing the speech signal when the level of the background noise is fluctuating will be demonstrated. The performance of the improved speech enhancement method will be compared with various spectral subtraction-based methods. [Work supported by NSF BCS0236707.
Automatic Barometric Updates from Ground-Based Navigational Aids
1990-03-12
ro fAutomatic Barometric Updates US Department from of Transportation Ground-Based Federal Aviation Administration Navigational Aids Office of Safety...tighter vertical spacing controls , particularly for operations near Terminal Control Areas (TCAs), Airport Radar Service Areas (ARSAs), military climb and...E.F., Ruth, J.C., and Williges, B.H. (1987). Speech Controls and Displays. In Salvendy, G., E. Handbook of Human Factors/Ergonomics, New York, John
Monaural room acoustic parameters from music and speech.
Kendrick, Paul; Cox, Trevor J; Li, Francis F; Zhang, Yonggang; Chambers, Jonathon A
2008-07-01
This paper compares two methods for extracting room acoustic parameters from reverberated speech and music. An approach which uses statistical machine learning, previously developed for speech, is extended to work with music. For speech, reverberation time estimations are within a perceptual difference limen of the true value. For music, virtually all early decay time estimations are within a difference limen of the true value. The estimation accuracy is not good enough in other cases due to differences between the simulated data set used to develop the empirical model and real rooms. The second method carries out a maximum likelihood estimation on decay phases at the end of notes or speech utterances. This paper extends the method to estimate parameters relating to the balance of early and late energies in the impulse response. For reverberation time and speech, the method provides estimations which are within the perceptual difference limen of the true value. For other parameters such as clarity, the estimations are not sufficiently accurate due to the natural reverberance of the excitation signals. Speech is a better test signal than music because of the greater periods of silence in the signal, although music is needed for low frequency measurement.
Visual-auditory integration during speech imitation in autism.
Williams, Justin H G; Massaro, Dominic W; Peel, Natalie J; Bosseler, Alexis; Suddendorf, Thomas
2004-01-01
Children with autistic spectrum disorder (ASD) may have poor audio-visual integration, possibly reflecting dysfunctional 'mirror neuron' systems which have been hypothesised to be at the core of the condition. In the present study, a computer program, utilizing speech synthesizer software and a 'virtual' head (Baldi), delivered speech stimuli for identification in auditory, visual or bimodal conditions. Children with ASD were poorer than controls at recognizing stimuli in the unimodal conditions, but once performance on this measure was controlled for, no group difference was found in the bimodal condition. A group of participants with ASD were also trained to develop their speech-reading ability. Training improved visual accuracy and this also improved the children's ability to utilize visual information in their processing of speech. Overall results were compared to predictions from mathematical models based on integration and non-integration, and were most consistent with the integration model. We conclude that, whilst they are less accurate in recognizing stimuli in the unimodal condition, children with ASD show normal integration of visual and auditory speech stimuli. Given that training in recognition of visual speech was effective, children with ASD may benefit from multi-modal approaches in imitative therapy and language training.
Ultrasound applicability in Speech Language Pathology and Audiology.
Barberena, Luciana da Silva; Brasil, Brunah de Castro; Melo, Roberta Michelon; Mezzomo, Carolina Lisbôa; Mota, Helena Bolli; Keske-Soares, Márcia
2014-01-01
To present recent studies that used the ultrasound in the fields of Speech Language Pathology and Audiology, which evidence possibilities of the applicability of this technique in different subareas. A bibliographic research was carried out in the PubMed database, using the keywords "ultrasonic," "speech," "phonetics," "Speech, Language and Hearing Sciences," "voice," "deglutition," and "myofunctional therapy," comprising some areas of Speech Language Pathology and Audiology Sciences. The keywords "ultrasound," "ultrasonography," "swallow," "orofacial myofunctional therapy," and "orofacial myology" were also used in the search. Studies in humans from the past 5 years were selected. In the preselection, duplicated studies, articles not fully available, and those that did not present direct relation between ultrasound and Speech Language Pathology and Audiology Sciences were discarded. The data were analyzed descriptively and classified subareas of Speech Language Pathology and Audiology Sciences. The following items were considered: purposes, participants, procedures, and results. We selected 12 articles for ultrasound versus speech/phonetics subarea, 5 for ultrasound versus voice, 1 for ultrasound versus muscles of mastication, and 10 for ultrasound versus swallow. Studies relating "ultrasound" and "Speech Language Pathology and Audiology Sciences" in the past 5 years were not found. Different studies on the use of ultrasound in Speech Language Pathology and Audiology Sciences were found. Each of them, according to its purpose, confirms new possibilities of the use of this instrument in the several subareas, aiming at a more accurate diagnosis and new evaluative and therapeutic possibilities.
The Promise of NLP and Speech Processing Technologies in Language Assessment
ERIC Educational Resources Information Center
Chapelle, Carol A.; Chung, Yoo-Ree
2010-01-01
Advances in natural language processing (NLP) and automatic speech recognition and processing technologies offer new opportunities for language testing. Despite their potential uses on a range of language test item types, relatively little work has been done in this area, and it is therefore not well understood by test developers, researchers or…
Learning L2 Pronunciation with a Mobile Speech Recognizer: French /y/
ERIC Educational Resources Information Center
Liakin, Denis; Cardoso, Walcir; Liakina, Natallia
2015-01-01
This study investigates the acquisition of the L2 French vowel /y/ in a mobile-assisted learning environment, via the use of automatic speech recognition (ASR). Particularly, it addresses the question of whether ASR-based pronunciation instruction using a mobile device can improve the production and perception of French /y/. Forty-two elementary…
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
ERIC Educational Resources Information Center
Anderson, Karen L.; Goldstein, Howard
2004-01-01
Children typically learn in classroom environments that have background noise and reverberation that interfere with accurate speech perception. Amplification technology can enhance the speech perception of students who are hard of hearing. Purpose: This study used a single-subject alternating treatments design to compare the speech recognition…
Computational validation of the motor contribution to speech perception.
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.
Digitised evaluation of speech intelligibility using vowels in maxillectomy patients.
Sumita, Y I; Hattori, M; Murase, M; Elbashti, M E; Taniguchi, H
2018-03-01
Among the functional disabilities that patients face following maxillectomy, speech impairment is a major factor influencing quality of life. Proper rehabilitation of speech, which may include prosthodontic and surgical treatments and speech therapy, requires accurate evaluation of speech intelligibility (SI). A simple, less time-consuming yet accurate evaluation is desirable both for maxillectomy patients and the various clinicians providing maxillofacial treatment. This study sought to determine the utility of digital acoustic analysis of vowels for the prediction of SI in maxillectomy patients, based on a comprehensive understanding of speech production in the vocal tract of maxillectomy patients and its perception. Speech samples were collected from 33 male maxillectomy patients (mean age 57.4 years) in two conditions, without and with a maxillofacial prosthesis, and formant data for the vowels /a/,/e/,/i/,/o/, and /u/ were calculated based on linear predictive coding. The frequency range of formant 2 (F2) was determined by differences between the minimum and maximum frequency. An SI test was also conducted to reveal the relationship between SI score and F2 range. Statistical analyses were applied. F2 range and SI score were significantly different between the two conditions without and with a prosthesis (both P < .0001). F2 range was significantly correlated with SI score in both the conditions (Spearman's r = .843, P < .0001; r = .832, P < .0001, respectively). These findings indicate that calculating the F2 range from 5 vowels has clinical utility for the prediction of SI after maxillectomy. © 2017 John Wiley & Sons Ltd.
Abnormal laughter-like vocalisations replacing speech in primary progressive aphasia
Rohrer, Jonathan D.; Warren, Jason D.; Rossor, Martin N.
2009-01-01
We describe ten patients with a clinical diagnosis of primary progressive aphasia (PPA) (pathologically confirmed in three cases) who developed abnormal laughter-like vocalisations in the context of progressive speech output impairment leading to mutism. Failure of speech output was accompanied by increasing frequency of the abnormal vocalisations until ultimately they constituted the patient's only extended utterance. The laughter-like vocalisations did not show contextual sensitivity but occurred as an automatic vocal output that replaced speech. Acoustic analysis of the vocalisations in two patients revealed abnormal motor features including variable note duration and inter-note interval, loss of temporal symmetry of laugh notes and loss of the normal decrescendo. Abnormal laughter-like vocalisations may be a hallmark of a subgroup in the PPA spectrum with impaired control and production of nonverbal vocal behaviour due to disruption of fronto-temporal networks mediating vocalisation. PMID:19435636
Fang, Chunying; Li, Haifeng; Ma, Lin; Zhang, Mancai
2017-01-01
Pathological speech usually refers to speech distortion resulting from illness or other biological insults. The assessment of pathological speech plays an important role in assisting the experts, while automatic evaluation of speech intelligibility is difficult because it is usually nonstationary and mutational. In this paper, we carry out an independent innovation of feature extraction and reduction, and we describe a multigranularity combined feature scheme which is optimized by the hierarchical visual method. A novel method of generating feature set based on S -transform and chaotic analysis is proposed. There are BAFS (430, basic acoustics feature), local spectral characteristics MSCC (84, Mel S -transform cepstrum coefficients), and chaotic features (12). Finally, radar chart and F -score are proposed to optimize the features by the hierarchical visual fusion. The feature set could be optimized from 526 to 96 dimensions based on NKI-CCRT corpus and 104 dimensions based on SVD corpus. The experimental results denote that new features by support vector machine (SVM) have the best performance, with a recognition rate of 84.4% on NKI-CCRT corpus and 78.7% on SVD corpus. The proposed method is thus approved to be effective and reliable for pathological speech intelligibility evaluation.
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.
Pathways of the inferior frontal occipital fasciculus in overt speech and reading.
Rollans, Claire; Cheema, Kulpreet; Georgiou, George K; Cummine, Jacqueline
2017-11-19
In this study, we examined the relationship between tractography-based measures of white matter integrity (ex. fractional anisotropy [FA]) from diffusion tensor imaging (DTI) and five reading-related tasks, including rapid automatized naming (RAN) of letters, digits, and objects, and reading of real words and nonwords. Twenty university students with no reported history of reading difficulties were tested on all five tasks and their performance was correlated with diffusion measures extracted through DTI tractography. A secondary analysis using whole-brain Tract-Based Spatial Statistics (TBSS) was also used to find clusters showing significant negative correlations between reaction time and FA. Results showed a significant relationship between the left inferior fronto-occipital fasciculus FA and performance on the RAN of objects task, as well as a strong relationship to nonword reading, which suggests a role for this tract in slower, non-automatic and/or resource-demanding speech tasks. There were no significant relationships between FA and the faster, more automatic speech tasks (RAN of letters and digits, and real word reading). These findings provide evidence for the role of the inferior fronto-occipital fasciculus in tasks that are highly demanding of orthography-phonology translation (e.g., nonword reading) and semantic processing (e.g., RAN object). This demonstrates the importance of the inferior fronto-occipital fasciculus in basic naming and suggests that this tract may be a sensitive predictor of rapid naming performance within the typical population. We discuss the findings in the context of current models of reading and speech production to further characterize the white matter pathways associated with basic reading processes. Copyright © 2017 IBRO. Published by Elsevier Ltd. All rights reserved.
The Effect of Feedback Schedule Manipulation on Speech Priming Patterns and Reaction Time
ERIC Educational Resources Information Center
Slocomb, Dana; Spencer, Kristie A.
2009-01-01
Speech priming tasks are frequently used to delineate stages in the speech process such as lexical retrieval and motor programming. These tasks, often measured in reaction time (RT), require fast and accurate responses, reflecting maximized participant performance, to result in robust priming effects. Encouraging speed and accuracy in responding…
Common cues to emotion in the dynamic facial expressions of speech and song
Livingstone, Steven R.; Thompson, William F.; Wanderley, Marcelo M.; Palmer, Caroline
2015-01-01
Speech and song are universal forms of vocalization that may share aspects of emotional expression. Research has focused on parallels in acoustic features, overlooking facial cues to emotion. In three experiments, we compared moving facial expressions in speech and song. In Experiment 1, vocalists spoke and sang statements each with five emotions. Vocalists exhibited emotion-dependent movements of the eyebrows and lip corners that transcended speech–song differences. Vocalists’ jaw movements were coupled to their acoustic intensity, exhibiting differences across emotion and speech–song. Vocalists’ emotional movements extended beyond vocal sound to include large sustained expressions, suggesting a communicative function. In Experiment 2, viewers judged silent videos of vocalists’ facial expressions prior to, during, and following vocalization. Emotional intentions were identified accurately for movements during and after vocalization, suggesting that these movements support the acoustic message. Experiment 3 compared emotional identification in voice-only, face-only, and face-and-voice recordings. Emotion judgements for voice-only singing were poorly identified, yet were accurate for all other conditions, confirming that facial expressions conveyed emotion more accurately than the voice in song, yet were equivalent in speech. Collectively, these findings highlight broad commonalities in the facial cues to emotion in speech and song, yet highlight differences in perception and acoustic-motor production. PMID:25424388
Speech rhythm alterations in Spanish-speaking individuals with Alzheimer's disease.
Martínez-Sánchez, Francisco; Meilán, Juan J G; Vera-Ferrandiz, Juan Antonio; Carro, Juan; Pujante-Valverde, Isabel M; Ivanova, Olga; Carcavilla, Nuria
2017-07-01
Rhythm is the speech property related to the temporal organization of sounds. Considerable evidence is now available for suggesting that dementia of Alzheimer's type is associated with impairments in speech rhythm. The aim of this study is to assess the use of an automatic computerized system for measuring speech rhythm characteristics in an oral reading task performed by 45 patients with Alzheimer's disease (AD) compared with those same characteristics among 82 healthy older adults without a diagnosis of dementia, and matched by age, sex and cultural background. Ranges of rhythmic-metric and clinical measurements were applied. The results show rhythmic differences between the groups, with higher variability of syllabic intervals in AD patients. Signal processing algorithms applied to oral reading recordings prove to be capable of differentiating between AD patients and older adults without dementia with an accuracy of 87% (specificity 81.7%, sensitivity 82.2%), based on the standard deviation of the duration of syllabic intervals. Experimental results show that the syllabic variability measurements extracted from the speech signal can be used to distinguish between older adults without a diagnosis of dementia and those with AD, and may be useful as a tool for the objective study and quantification of speech deficits in AD.
A Generative Model of Speech Production in Broca’s and Wernicke’s Areas
Price, Cathy J.; Crinion, Jenny T.; MacSweeney, Mairéad
2011-01-01
Speech production involves the generation of an auditory signal from the articulators and vocal tract. When the intended auditory signal does not match the produced sounds, subsequent articulatory commands can be adjusted to reduce the difference between the intended and produced sounds. This requires an internal model of the intended speech output that can be compared to the produced speech. The aim of this functional imaging study was to identify brain activation related to the internal model of speech production after activation related to vocalization, auditory feedback, and movement in the articulators had been controlled. There were four conditions: silent articulation of speech, non-speech mouth movements, finger tapping, and visual fixation. In the speech conditions, participants produced the mouth movements associated with the words “one” and “three.” We eliminated auditory feedback from the spoken output by instructing participants to articulate these words without producing any sound. The non-speech mouth movement conditions involved lip pursing and tongue protrusions to control for movement in the articulators. The main difference between our speech and non-speech mouth movement conditions is that prior experience producing speech sounds leads to the automatic and covert generation of auditory and phonological associations that may play a role in predicting auditory feedback. We found that, relative to non-speech mouth movements, silent speech activated Broca’s area in the left dorsal pars opercularis and Wernicke’s area in the left posterior superior temporal sulcus. We discuss these results in the context of a generative model of speech production and propose that Broca’s and Wernicke’s areas may be involved in predicting the speech output that follows articulation. These predictions could provide a mechanism by which rapid movement of the articulators is precisely matched to the intended speech outputs during future articulations
NASA Technical Reports Server (NTRS)
Sandor, A.; Moses, H. R.
2016-01-01
asked to identify the alert as quickly and as accurately as possible. Reaction time and accuracy were measured. Participants identified speech alerts significantly faster than tone alerts. The HERA study investigated the performance of participants in a flight-like environment. Participants were instructed to complete items on a task list and respond to C&W alerts as they occurred. Reaction time and accuracy were measured to determine if the benefits of speech alarms are still present in an applied setting.
Transcribe Your Class: Using Speech Recognition to Improve Access for At-Risk Students
ERIC Educational Resources Information Center
Bain, Keith; Lund-Lucas, Eunice; Stevens, Janice
2012-01-01
Through a project supported by Canada's Social Development Partnerships Program, a team of leading National Disability Organizations, universities, and industry partners are piloting a prototype Hosted Transcription Service that uses speech recognition to automatically create multimedia transcripts that can be used by students for study purposes.…
A voice-input voice-output communication aid for people with severe speech impairment.
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.
Hakvoort, Britt; de Bree, Elise; van der Leij, Aryan; Maassen, Ben; van Setten, Ellie; Maurits, Natasha; van Zuijen, Titia L
2016-12-01
This study assessed whether a categorical speech perception (CP) deficit is associated with dyslexia or familial risk for dyslexia, by exploring a possible cascading relation from speech perception to phonology to reading and by identifying whether speech perception distinguishes familial risk (FR) children with dyslexia (FRD) from those without dyslexia (FRND). Data were collected from 9-year-old FRD (n = 37) and FRND (n = 41) children and age-matched controls (n = 49) on CP identification and discrimination and on the phonological processing measures rapid automatized naming, phoneme awareness, and nonword repetition. The FRD group performed more poorly on CP than the FRND and control groups. Findings on phonological processing align with the literature in that (a) phonological processing related to reading and (b) the FRD group showed the lowest phonological processing outcomes. Furthermore, CP correlated weakly with reading, but this relationship was fully mediated by rapid automatized naming. Although CP phonological skills are related to dyslexia, there was no strong evidence for a cascade from CP to phonology to reading. Deficits in CP at the behavioral level are not directly associated with dyslexia.
Toward dynamic magnetic resonance imaging of the vocal tract during speech production.
Ventura, Sandra M Rua; Freitas, Diamantino Rui S; Tavares, João Manuel R S
2011-07-01
The most recent and significant magnetic resonance imaging (MRI) improvements allow for the visualization of the vocal tract during speech production, which has been revealed to be a powerful tool in dynamic speech research. However, a synchronization technique with enhanced temporal resolution is still required. The study design was transversal in nature. Throughout this work, a technique for the dynamic study of the vocal tract with MRI by using the heart's signal to synchronize and trigger the imaging-acquisition process is presented and described. The technique in question is then used in the measurement of four speech articulatory parameters to assess three different syllables (articulatory gestures) of European Portuguese Language. The acquired MR images are automatically reconstructed so as to result in a variable sequence of images (slices) of different vocal tract shapes in articulatory positions associated with Portuguese speech sounds. The knowledge obtained as a result of the proposed technique represents a direct contribution to the improvement of speech synthesis algorithms, thereby allowing for novel perceptions in coarticulation studies, in addition to providing further efficient clinical guidelines in the pursuit of more proficient speech rehabilitation processes. Copyright © 2011 The Voice Foundation. Published by Mosby, Inc. All rights reserved.
Fitmunk: improving protein structures by accurate, automatic modeling of side-chain conformations.
Porebski, Przemyslaw Jerzy; Cymborowski, Marcin; Pasenkiewicz-Gierula, Marta; Minor, Wladek
2016-02-01
Improvements in crystallographic hardware and software have allowed automated structure-solution pipelines to approach a near-`one-click' experience for the initial determination of macromolecular structures. However, in many cases the resulting initial model requires a laborious, iterative process of refinement and validation. A new method has been developed for the automatic modeling of side-chain conformations that takes advantage of rotamer-prediction methods in a crystallographic context. The algorithm, which is based on deterministic dead-end elimination (DEE) theory, uses new dense conformer libraries and a hybrid energy function derived from experimental data and prior information about rotamer frequencies to find the optimal conformation of each side chain. In contrast to existing methods, which incorporate the electron-density term into protein-modeling frameworks, the proposed algorithm is designed to take advantage of the highly discriminatory nature of electron-density maps. This method has been implemented in the program Fitmunk, which uses extensive conformational sampling. This improves the accuracy of the modeling and makes it a versatile tool for crystallographic model building, refinement and validation. Fitmunk was extensively tested on over 115 new structures, as well as a subset of 1100 structures from the PDB. It is demonstrated that the ability of Fitmunk to model more than 95% of side chains accurately is beneficial for improving the quality of crystallographic protein models, especially at medium and low resolutions. Fitmunk can be used for model validation of existing structures and as a tool to assess whether side chains are modeled optimally or could be better fitted into electron density. Fitmunk is available as a web service at http://kniahini.med.virginia.edu/fitmunk/server/ or at http://fitmunk.bitbucket.org/.
Knipfer, Christian; Riemann, Max; Bocklet, Tobias; Noeth, Elmar; Schuster, Maria; Sokol, Biljana; Eitner, Stephan; Nkenke, Emeka; Stelzle, Florian
2014-01-01
Tooth loss and its prosthetic rehabilitation significantly affect speech intelligibility. However, little is known about the influence of speech deficiencies on oral health-related quality of life (OHRQoL). The aim of this study was to investigate whether speech intelligibility enhancement through prosthetic rehabilitation significantly influences OHRQoL in patients wearing complete maxillary dentures. Speech intelligibility by means of an automatic speech recognition system (ASR) was prospectively evaluated and compared with subjectively assessed Oral Health Impact Profile (OHIP) scores. Speech was recorded in 28 edentulous patients 1 week prior to the fabrication of new complete maxillary dentures and 6 months thereafter. Speech intelligibility was computed based on the word accuracy (WA) by means of an ASR and compared with a matched control group. One week before and 6 months after rehabilitation, patients assessed themselves for OHRQoL. Speech intelligibility improved significantly after 6 months. Subjects reported a significantly higher OHRQoL after maxillary rehabilitation with complete dentures. No significant correlation was found between the OHIP sum score or its subscales to the WA. Speech intelligibility enhancement achieved through the fabrication of new complete maxillary dentures might not be in the forefront of the patients' perception of their quality of life. For the improvement of OHRQoL in patients wearing complete maxillary dentures, food intake and mastication as well as freedom from pain play a more prominent role.
Walenski, Matthew; Swinney, David
2009-01-01
The central question underlying this study revolves around how children process co-reference relationships—such as those evidenced by pronouns (him) and reflexives (himself)—and how a slowed rate of speech input may critically affect this process. Previous studies of child language processing have demonstrated that typical language developing (TLD) children as young as 4 years of age process co-reference relations in a manner similar to adults on-line. In contrast, off-line measures of pronoun comprehension suggest a developmental delay for pronouns (relative to reflexives). The present study examines dependency relations in TLD children (ages 5–13) and investigates how a slowed rate of speech input affects the unconscious (on-line) and conscious (off-line) parsing of these constructions. For the on-line investigations (using a cross-modal picture priming paradigm), results indicate that at a normal rate of speech TLD children demonstrate adult-like syntactic reflexes. At a slowed rate of speech the typical language developing children displayed a breakdown in automatic syntactic parsing (again, similar to the pattern seen in unimpaired adults). As demonstrated in the literature, our off-line investigations (sentence/picture matching task) revealed that these children performed much better on reflexives than on pronouns at a regular speech rate. However, at the slow speech rate, performance on pronouns was substantially improved, whereas performance on reflexives was not different than at the regular speech rate. We interpret these results in light of a distinction between fast automatic processes (relied upon for on-line processing in real time) and conscious reflective processes (relied upon for off-line processing), such that slowed speech input disrupts the former, yet improves the latter. PMID:19343495
ERIC Educational Resources Information Center
De Felice, Rachele; Deane, Paul
2012-01-01
This study proposes an approach to automatically score the "TOEIC"® Writing e-mail task. We focus on one component of the scoring rubric, which notes whether the test-takers have used particular speech acts such as requests, orders, or commitments. We developed a computational model for automated speech act identification and tested it…
Methods for eliciting, annotating, and analyzing databases for child speech development.
Beckman, Mary E; Plummer, Andrew R; Munson, Benjamin; Reidy, Patrick F
2017-09-01
Methods from automatic speech recognition (ASR), such as segmentation and forced alignment, have facilitated the rapid annotation and analysis of very large adult speech databases and databases of caregiver-infant interaction, enabling advances in speech science that were unimaginable just a few decades ago. This paper centers on two main problems that must be addressed in order to have analogous resources for developing and exploiting databases of young children's speech. The first problem is to understand and appreciate the differences between adult and child speech that cause ASR models developed for adult speech to fail when applied to child speech. These differences include the fact that children's vocal tracts are smaller than those of adult males and also changing rapidly in size and shape over the course of development, leading to between-talker variability across age groups that dwarfs the between-talker differences between adult men and women. Moreover, children do not achieve fully adult-like speech motor control until they are young adults, and their vocabularies and phonological proficiency are developing as well, leading to considerably more within-talker variability as well as more between-talker variability. The second problem then is to determine what annotation schemas and analysis techniques can most usefully capture relevant aspects of this variability. Indeed, standard acoustic characterizations applied to child speech reveal that adult-centered annotation schemas fail to capture phenomena such as the emergence of covert contrasts in children's developing phonological systems, while also revealing children's nonuniform progression toward community speech norms as they acquire the phonological systems of their native languages. Both problems point to the need for more basic research into the growth and development of the articulatory system (as well as of the lexicon and phonological system) that is oriented explicitly toward the construction of
Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos
2014-01-01
Assessing the structural integrity of the hippocampus (HC) is an essential step toward prevention, diagnosis, and follow-up of various brain disorders due to the implication of the structural changes of the HC in those disorders. In this respect, the development of automatic segmentation methods that can accurately, reliably, and reproducibly segment the HC has attracted considerable attention over the past decades. This paper presents an innovative 3-D fully automatic method to be used on top of the multiatlas concept for the HC segmentation. The method is based on a subject-specific set of 3-D optimal local maps (OLMs) that locally control the influence of each energy term of a hybrid active contour model (ACM). The complete set of the OLMs for a set of training images is defined simultaneously via an optimization scheme. At the same time, the optimal ACM parameters are also calculated. Therefore, heuristic parameter fine-tuning is not required. Training OLMs are subsequently combined, by applying an extended multiatlas concept, to produce the OLMs that are anatomically more suitable to the test image. The proposed algorithm was tested on three different and publicly available data sets. Its accuracy was compared with that of state-of-the-art methods demonstrating the efficacy and robustness of the proposed method. PMID:27170866
Pathological speech signal analysis and classification using empirical mode decomposition.
Kaleem, Muhammad; Ghoraani, Behnaz; Guergachi, Aziz; Krishnan, Sridhar
2013-07-01
Automated classification of normal and pathological speech signals can provide an objective and accurate mechanism for pathological speech diagnosis, and is an active area of research. A large part of this research is based on analysis of acoustic measures extracted from sustained vowels. However, sustained vowels do not reflect real-world attributes of voice as effectively as continuous speech, which can take into account important attributes of speech such as rapid voice onset and termination, changes in voice frequency and amplitude, and sudden discontinuities in speech. This paper presents a methodology based on empirical mode decomposition (EMD) for classification of continuous normal and pathological speech signals obtained from a well-known database. EMD is used to decompose randomly chosen portions of speech signals into intrinsic mode functions, which are then analyzed to extract meaningful temporal and spectral features, including true instantaneous features which can capture discriminative information in signals hidden at local time-scales. A total of six features are extracted, and a linear classifier is used with the feature vector to classify continuous speech portions obtained from a database consisting of 51 normal and 161 pathological speakers. A classification accuracy of 95.7 % is obtained, thus demonstrating the effectiveness of the methodology.
Temporal processing of speech in a time-feature space
NASA Astrophysics Data System (ADS)
Avendano, Carlos
1997-09-01
reverberation for speech enhancement, and improvements on automatic recognition of speech degraded by linear distortions and reverberation.
McNeil, M.R.; Katz, W.F.; Fossett, T.R.D.; Garst, D.M.; Szuminsky, N.J.; Carter, G.; Lim, K.Y.
2010-01-01
Apraxia of speech (AOS) is a motor speech disorder characterized by disturbed spatial and temporal parameters of movement. Research on motor learning suggests that augmented feedback may provide a beneficial effect for training movement. This study examined the effects of the presence and frequency of online augmented visual kinematic feedback (AVKF) and clinician-provided perceptual feedback on speech accuracy in 2 adults with acquired AOS. Within a single-subject multiple-baseline design, AVKF was provided using electromagnetic midsagittal articulography (EMA) in 2 feedback conditions (50 or 100%). Articulator placement was specified for speech motor targets (SMTs). Treated and baselined SMTs were in the initial or final position of single-syllable words, in varying consonant-vowel or vowel-consonant contexts. SMTs were selected based on each participant's pre-assessed erred productions. Productions were digitally recorded and online perceptual judgments of accuracy (including segment and intersegment distortions) were made. Inter- and intra-judge reliability for perceptual accuracy was high. Results measured by visual inspection and effect size revealed positive acquisition and generalization effects for both participants. Generalization occurred across vowel contexts and to untreated probes. Results of the frequency manipulation were confounded by presentation order. Maintenance of learned and generalized effects were demonstrated for 1 participant. These data provide support for the role of augmented feedback in treating speech movements that result in perceptually accurate speech production. Future investigations will explore the independent contributions of each feedback type (i.e. kinematic and perceptual) in producing efficient and effective training of SMTs in persons with AOS. PMID:20424468
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.
Heimbauer, Lisa A; Beran, Michael J; Owren, Michael J
2011-07-26
A long-standing debate concerns whether humans are specialized for speech perception, which some researchers argue is demonstrated by the ability to understand synthetic speech with significantly reduced acoustic cues to phonetic content. We tested a chimpanzee (Pan troglodytes) that recognizes 128 spoken words, asking whether she could understand such speech. Three experiments presented 48 individual words, with the animal selecting a corresponding visuographic symbol from among four alternatives. Experiment 1 tested spectrally reduced, noise-vocoded (NV) synthesis, originally developed to simulate input received by human cochlear-implant users. Experiment 2 tested "impossibly unspeechlike" sine-wave (SW) synthesis, which reduces speech to just three moving tones. Although receiving only intermittent and noncontingent reward, the chimpanzee performed well above chance level, including when hearing synthetic versions for the first time. Recognition of SW words was least accurate but improved in experiment 3 when natural words in the same session were rewarded. The chimpanzee was more accurate with NV than SW versions, as were 32 human participants hearing these items. The chimpanzee's ability to spontaneously recognize acoustically reduced synthetic words suggests that experience rather than specialization is critical for speech-perception capabilities that some have suggested are uniquely human. Copyright © 2011 Elsevier Ltd. All rights reserved.
Automatic measurement of voice onset time using discriminative structured prediction.
Sonderegger, Morgan; Keshet, Joseph
2012-12-01
A discriminative large-margin algorithm for automatic measurement of voice onset time (VOT) is described, considered as a case of predicting structured output from speech. Manually labeled data are used to train a function that takes as input a speech segment of an arbitrary length containing a voiceless stop, and outputs its VOT. The function is explicitly trained to minimize the difference between predicted and manually measured VOT; it operates on a set of acoustic feature functions designed based on spectral and temporal cues used by human VOT annotators. The algorithm is applied to initial voiceless stops from four corpora, representing different types of speech. Using several evaluation methods, the algorithm's performance is near human intertranscriber reliability, and compares favorably with previous work. Furthermore, the algorithm's performance is minimally affected by training and testing on different corpora, and remains essentially constant as the amount of training data is reduced to 50-250 manually labeled examples, demonstrating the method's practical applicability to new datasets.
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
Neural Recruitment for the Production of Native and Novel Speech Sounds
Moser, Dana; Fridriksson, Julius; Bonilha, Leonardo; Healy, Eric W.; Baylis, Gordon; Baker, Julie; Rorden, Chris
2010-01-01
Two primary areas of damage have been implicated in apraxia of speech (AOS) based on the time post-stroke: (1) the left inferior frontal gyrus (IFG) in acute patients, and (2) the left anterior insula (aIns) in chronic patients. While AOS is widely characterized as a disorder in motor speech planning, little is known about the specific contributions of each of these regions in speech. The purpose of this study was to investigate cortical activation during speech production with a specific focus on the aIns and the IFG in normal adults. While undergoing sparse fMRI, 30 normal adults completed a 30-minute speech-repetition task consisting of three-syllable nonwords that contained either (a) English (native) syllables or (b) Non-English (novel) syllables. When the novel syllable productions were compared to the native syllable productions, greater neural activation was observed in the aIns and IFG, particularly during the first 10 minutes of the task when novelty was the greatest. Although activation in the aIns remained high throughout the task for novel productions, greater activation was clearly demonstrated when the initial 10 minutes were compared to the final 10 minutes of the task. These results suggest increased activity within an extensive neural network, including the aIns and IFG, when the motor speech system is taxed, such as during the production of novel speech. We speculate that the amount of left aIns recruitment during speech production may be related to the internal construction of the motor speech unit such that the degree of novelty/automaticity would result in more or less demands respectively. The role of the IFG as a storehouse and integrative processor for previously acquired routines is also discussed. PMID:19385020
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
How much is a word? Predicting ease of articulation planning from apraxic speech error patterns.
Ziegler, Wolfram; Aichert, Ingrid
2015-08-01
According to intuitive concepts, 'ease of articulation' is influenced by factors like word length or the presence of consonant clusters in an utterance. Imaging studies of speech motor control use these factors to systematically tax the speech motor system. Evidence from apraxia of speech, a disorder supposed to result from speech motor planning impairment after lesions to speech motor centers in the left hemisphere, supports the relevance of these and other factors in disordered speech planning and the genesis of apraxic speech errors. Yet, there is no unified account of the structural properties rendering a word easy or difficult to pronounce. To model the motor planning demands of word articulation by a nonlinear regression model trained to predict the likelihood of accurate word production in apraxia of speech. We used a tree-structure model in which vocal tract gestures are embedded in hierarchically nested prosodic domains to derive a recursive set of terms for the computation of the likelihood of accurate word production. The model was trained with accuracy data from a set of 136 words averaged over 66 samples from apraxic speakers. In a second step, the model coefficients were used to predict a test dataset of accuracy values for 96 new words, averaged over 120 samples produced by a different group of apraxic speakers. Accurate modeling of the first dataset was achieved in the training study (R(2)adj = .71). In the cross-validation, the test dataset was predicted with a high accuracy as well (R(2)adj = .67). The model shape, as reflected by the coefficient estimates, was consistent with current phonetic theories and with clinical evidence. In accordance with phonetic and psycholinguistic work, a strong influence of word stress on articulation errors was found. The proposed model provides a unified and transparent account of the motor planning requirements of word articulation. Copyright © 2015 Elsevier Ltd. All rights reserved.
Sound and speech detection and classification in a Health Smart Home.
Fleury, A; Noury, N; Vacher, M; Glasson, H; Seri, J F
2008-01-01
Improvements in medicine increase life expectancy in the world and create a new bottleneck at the entrance of specialized and equipped institutions. To allow elderly people to stay at home, researchers work on ways to monitor them in their own environment, with non-invasive sensors. To meet this goal, smart homes, equipped with lots of sensors, deliver information on the activities of the person and can help detect distress situations. In this paper, we present a global speech and sound recognition system that can be set-up in a flat. We placed eight microphones in the Health Smart Home of Grenoble (a real living flat of 47m(2)) and we automatically analyze and sort out the different sounds recorded in the flat and the speech uttered (to detect normal or distress french sentences). We introduce the methods for the sound and speech recognition, the post-processing of the data and finally the experimental results obtained in real conditions in the flat.
Inner Speech's Relationship With Overt Speech in Poststroke Aphasia.
Stark, Brielle C; Geva, Sharon; Warburton, Elizabeth A
2017-09-18
Relatively preserved inner speech alongside poor overt speech has been documented in some persons with aphasia (PWA), but the relationship of overt speech with inner speech is still largely unclear, as few studies have directly investigated these factors. The present study investigates the relationship of relatively preserved inner speech in aphasia with selected measures of language and cognition. Thirty-eight persons with chronic aphasia (27 men, 11 women; average age 64.53 ± 13.29 years, time since stroke 8-111 months) were classified as having relatively preserved inner and overt speech (n = 21), relatively preserved inner speech with poor overt speech (n = 8), or not classified due to insufficient measurements of inner and/or overt speech (n = 9). Inner speech scores (by group) were correlated with selected measures of language and cognition from the Comprehensive Aphasia Test (Swinburn, Porter, & Al, 2004). The group with poor overt speech showed a significant relationship of inner speech with overt naming (r = .95, p < .01) and with mean length of utterance produced during a written picture description (r = .96, p < .01). Correlations between inner speech and language and cognition factors were not significant for the group with relatively good overt speech. As in previous research, we show that relatively preserved inner speech is found alongside otherwise severe production deficits in PWA. PWA with poor overt speech may rely more on preserved inner speech for overt picture naming (perhaps due to shared resources with verbal working memory) and for written picture description (perhaps due to reliance on inner speech due to perceived task difficulty). Assessments of inner speech may be useful as a standard component of aphasia screening, and therapy focused on improving and using inner speech may prove clinically worthwhile. https://doi.org/10.23641/asha.5303542.
Namasivayam, Aravind Kumar; Pukonen, Margit; Goshulak, Debra; Yu, Vickie Y; Kadis, Darren S; Kroll, Robert; Pang, Elizabeth W; De Nil, Luc F
2013-01-01
The current study was undertaken to investigate the impact of speech motor issues on the speech intelligibility of children with moderate to severe speech sound disorders (SSD) within the context of the PROMPT intervention approach. The word-level Children's Speech Intelligibility Measure (CSIM), the sentence-level Beginner's Intelligibility Test (BIT) and tests of speech motor control and articulation proficiency were administered to 12 children (3:11 to 6:7 years) before and after PROMPT therapy. PROMPT treatment was provided for 45 min twice a week for 8 weeks. Twenty-four naïve adult listeners aged 22-46 years judged the intelligibility of the words and sentences. For CSIM, each time a recorded word was played to the listeners they were asked to look at a list of 12 words (multiple-choice format) and circle the word while for BIT sentences, the listeners were asked to write down everything they heard. Words correctly circled (CSIM) or transcribed (BIT) were averaged across three naïve judges to calculate percentage speech intelligibility. Speech intelligibility at both the word and sentence level was significantly correlated with speech motor control, but not articulatory proficiency. Further, the severity of speech motor planning and sequencing issues may potentially be a limiting factor in connected speech intelligibility and highlights the need to target these issues early and directly in treatment. The reader will be able to: (1) outline the advantages and disadvantages of using word- and sentence-level speech intelligibility tests; (2) describe the impact of speech motor control and articulatory proficiency on speech intelligibility; and (3) describe how speech motor control and speech intelligibility data may provide critical information to aid treatment planning. Copyright © 2013 Elsevier Inc. All rights reserved.
Stoliarova, L G; Varakin, Iu Ia; Vavilov, S B
1981-01-01
Clinical and tomographic examinations of 40 patients with aphasia developed after an ischemic stroke were carried out. In more than half of them no correlation between the aphasia gravity and character on the one hand, and the size and localization of the ischemic focus (or foci) in the brain on the other was noted. With similar character and gravity of the speech disorder the size and localization of the ischemic foci may be different, ad vice versa. It has been shown that the interrelations between the focal pathology of the brain and the character and gravity of speech disorders are very complicated. One should take into consideration the possibility of individual organization of the speech functions, the degree of the speech activity automatism before the disease, and the state of the cerebrovascular system as a whole.
An acoustic feature-based similarity scoring system for speech rehabilitation assistance.
Syauqy, Dahnial; Wu, Chao-Min; Setyawati, Onny
2016-08-01
The purpose of this study is to develop a tool to assist speech therapy and rehabilitation, which focused on automatic scoring based on the comparison of the patient's speech with another normal speech on several aspects including pitch, vowel, voiced-unvoiced segments, strident fricative and sound intensity. The pitch estimation employed the use of cepstrum-based algorithm for its robustness; the vowel classification used multilayer perceptron (MLP) to classify vowel from pitch and formants; and the strident fricative detection was based on the major peak spectral intensity, location and the pitch existence in the segment. In order to evaluate the performance of the system, this study analyzed eight patient's speech recordings (four males, four females; 4-58-years-old), which had been recorded in previous study in cooperation with Taipei Veterans General Hospital and Taoyuan General Hospital. The experiment result on pitch algorithm showed that the cepstrum method had 5.3% of gross pitch error from a total of 2086 frames. On the vowel classification algorithm, MLP method provided 93% accuracy (men), 87% (women) and 84% (children). In total, the overall results showed that 156 tool's grading results (81%) were consistent compared to 192 audio and visual observations done by four experienced respondents. Implication for Rehabilitation Difficulties in communication may limit the ability of a person to transfer and exchange information. The fact that speech is one of the primary means of communication has encouraged the needs of speech diagnosis and rehabilitation. The advances of technology in computer-assisted speech therapy (CAST) improve the quality, time efficiency of the diagnosis and treatment of the disorders. The present study attempted to develop tool to assist speech therapy and rehabilitation, which provided simple interface to let the assessment be done even by the patient himself without the need of particular knowledge of speech processing while at the
Scarbel, Lucie; Beautemps, Denis; Schwartz, Jean-Luc; Sato, Marc
2017-07-01
Speech communication can be viewed as an interactive process involving a functional coupling between sensory and motor systems. One striking example comes from phonetic convergence, when speakers automatically tend to mimic their interlocutor's speech during communicative interaction. The goal of this study was to investigate sensory-motor linkage in speech production in postlingually deaf cochlear implanted participants and normal hearing elderly adults through phonetic convergence and imitation. To this aim, two vowel production tasks, with or without instruction to imitate an acoustic vowel, were proposed to three groups of young adults with normal hearing, elderly adults with normal hearing and post-lingually deaf cochlear-implanted patients. Measure of the deviation of each participant's f 0 from their own mean f 0 was measured to evaluate the ability to converge to each acoustic target. showed that cochlear-implanted participants have the ability to converge to an acoustic target, both intentionally and unintentionally, albeit with a lower degree than young and elderly participants with normal hearing. By providing evidence for phonetic convergence and speech imitation, these results suggest that, as in young adults, perceptuo-motor relationships are efficient in elderly adults with normal hearing and that cochlear-implanted adults recovered significant perceptuo-motor abilities following cochlear implantation. Copyright © 2017 Elsevier Ltd. All rights reserved.
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.
Speech waveform perturbation analysis: a perceptual-acoustical comparison of seven measures.
Askenfelt, A G; Hammarberg, B
1986-03-01
The performance of seven acoustic measures of cycle-to-cycle variations (perturbations) in the speech waveform was compared. All measures were calculated automatically and applied on running speech. Three of the measures refer to the frequency of occurrence and severity of waveform perturbations in special selected parts of the speech, identified by means of the rate of change in the fundamental frequency. Three other measures refer to statistical properties of the distribution of the relative frequency differences between adjacent pitch periods. One perturbation measure refers to the percentage of consecutive pitch period differences with alternating signs. The acoustic measures were tested on tape recorded speech samples from 41 voice patients, before and after successful therapy. Scattergrams of acoustic waveform perturbation data versus an average of perceived deviant voice qualities, as rated by voice clinicians, are presented. The perturbation measures were compared with regard to the acoustic-perceptual correlation and their ability to discriminate between normal and pathological voice status. The standard deviation of the distribution of the relative frequency differences was suggested as the most useful acoustic measure of waveform perturbations for clinical applications.
Development of a Low-Cost, Noninvasive, Portable Visual Speech Recognition Program.
Kohlberg, Gavriel D; Gal, Ya'akov Kobi; Lalwani, Anil K
2016-09-01
Loss of speech following tracheostomy and laryngectomy severely limits communication to simple gestures and facial expressions that are largely ineffective. To facilitate communication in these patients, we seek to develop a low-cost, noninvasive, portable, and simple visual speech recognition program (VSRP) to convert articulatory facial movements into speech. A Microsoft Kinect-based VSRP was developed to capture spatial coordinates of lip movements and translate them into speech. The articulatory speech movements associated with 12 sentences were used to train an artificial neural network classifier. The accuracy of the classifier was then evaluated on a separate, previously unseen set of articulatory speech movements. The VSRP was successfully implemented and tested in 5 subjects. It achieved an accuracy rate of 77.2% (65.0%-87.6% for the 5 speakers) on a 12-sentence data set. The mean time to classify an individual sentence was 2.03 milliseconds (1.91-2.16). We have demonstrated the feasibility of a low-cost, noninvasive, portable VSRP based on Kinect to accurately predict speech from articulation movements in clinically trivial time. This VSRP could be used as a novel communication device for aphonic patients. © The Author(s) 2016.
Schädler, Marc René; Kollmeier, Birger
2015-04-01
To test if simultaneous spectral and temporal processing is required to extract robust features for automatic speech recognition (ASR), the robust spectro-temporal two-dimensional-Gabor filter bank (GBFB) front-end from Schädler, Meyer, and Kollmeier [J. Acoust. Soc. Am. 131, 4134-4151 (2012)] was de-composed into a spectral one-dimensional-Gabor filter bank and a temporal one-dimensional-Gabor filter bank. A feature set that is extracted with these separate spectral and temporal modulation filter banks was introduced, the separate Gabor filter bank (SGBFB) features, and evaluated on the CHiME (Computational Hearing in Multisource Environments) keywords-in-noise recognition task. From the perspective of robust ASR, the results showed that spectral and temporal processing can be performed independently and are not required to interact with each other. Using SGBFB features permitted the signal-to-noise ratio (SNR) to be lowered by 1.2 dB while still performing as well as the GBFB-based reference system, which corresponds to a relative improvement of the word error rate by 12.8%. Additionally, the real time factor of the spectro-temporal processing could be reduced by more than an order of magnitude. Compared to human listeners, the SNR needed to be 13 dB higher when using Mel-frequency cepstral coefficient features, 11 dB higher when using GBFB features, and 9 dB higher when using SGBFB features to achieve the same recognition performance.
Ylinen, Sari; Nora, Anni; Leminen, Alina; Hakala, Tero; Huotilainen, Minna; Shtyrov, Yury; Mäkelä, Jyrki P; Service, Elisabet
2015-06-01
Speech production, both overt and covert, down-regulates the activation of auditory cortex. This is thought to be due to forward prediction of the sensory consequences of speech, contributing to a feedback control mechanism for speech production. Critically, however, these regulatory effects should be specific to speech content to enable accurate speech monitoring. To determine the extent to which such forward prediction is content-specific, we recorded the brain's neuromagnetic responses to heard multisyllabic pseudowords during covert rehearsal in working memory, contrasted with a control task. The cortical auditory processing of target syllables was significantly suppressed during rehearsal compared with control, but only when they matched the rehearsed items. This critical specificity to speech content enables accurate speech monitoring by forward prediction, as proposed by current models of speech production. The one-to-one phonological motor-to-auditory mappings also appear to serve the maintenance of information in phonological working memory. Further findings of right-hemispheric suppression in the case of whole-item matches and left-hemispheric enhancement for last-syllable mismatches suggest that speech production is monitored by 2 auditory-motor circuits operating on different timescales: Finer grain in the left versus coarser grain in the right hemisphere. Taken together, our findings provide hemisphere-specific evidence of the interface between inner and heard speech. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
NASA Astrophysics Data System (ADS)
Morishima, Shigeo; Nakamura, Satoshi
2004-12-01
We introduce a multimodal English-to-Japanese and Japanese-to-English translation system that also translates the speaker's speech motion by synchronizing it to the translated speech. This system also introduces both a face synthesis technique that can generate any viseme lip shape and a face tracking technique that can estimate the original position and rotation of a speaker's face in an image sequence. To retain the speaker's facial expression, we substitute only the speech organ's image with the synthesized one, which is made by a 3D wire-frame model that is adaptable to any speaker. Our approach provides translated image synthesis with an extremely small database. The tracking motion of the face from a video image is performed by template matching. In this system, the translation and rotation of the face are detected by using a 3D personal face model whose texture is captured from a video frame. We also propose a method to customize the personal face model by using our GUI tool. By combining these techniques and the translated voice synthesis technique, an automatic multimodal translation can be achieved that is suitable for video mail or automatic dubbing systems into other languages.
Modeling Co-evolution of Speech and Biology.
de Boer, Bart
2016-04-01
Two computer simulations are investigated that model interaction of cultural evolution of language and biological evolution of adaptations to language. Both are agent-based models in which a population of agents imitates each other using realistic vowels. The agents evolve under selective pressure for good imitation. In one model, the evolution of the vocal tract is modeled; in the other, a cognitive mechanism for perceiving speech accurately is modeled. In both cases, biological adaptations to using and learning speech evolve, even though the system of speech sounds itself changes at a more rapid time scale than biological evolution. However, the fact that the available acoustic space is used maximally (a self-organized result of cultural evolution) is constant, and therefore biological evolution does have a stable target. This work shows that when cultural and biological traits are continuous, their co-evolution may lead to cognitive adaptations that are strong enough to detect empirically. Copyright © 2016 Cognitive Science Society, Inc.
Automatic speech recognition research at NASA-Ames Research Center
NASA Technical Reports Server (NTRS)
Coler, Clayton R.; Plummer, Robert P.; Huff, Edward M.; Hitchcock, Myron H.
1977-01-01
A trainable acoustic pattern recognizer manufactured by Scope Electronics is presented. The voice command system VCS encodes speech by sampling 16 bandpass filters with center frequencies in the range from 200 to 5000 Hz. Variations in speaking rate are compensated for by a compression algorithm that subdivides each utterance into eight subintervals in such a way that the amount of spectral change within each subinterval is the same. The recorded filter values within each subinterval are then reduced to a 15-bit representation, giving a 120-bit encoding for each utterance. The VCS incorporates a simple recognition algorithm that utilizes five training samples of each word in a vocabulary of up to 24 words. The recognition rate of approximately 85 percent correct for untrained speakers and 94 percent correct for trained speakers was not considered adequate for flight systems use. Therefore, the built-in recognition algorithm was disabled, and the VCS was modified to transmit 120-bit encodings to an external computer for recognition.
Histogram equalization with Bayesian estimation for noise robust speech recognition.
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.
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.
Helium Speech: An Application of Standing Waves
ERIC Educational Resources Information Center
Wentworth, Christopher D.
2011-01-01
Taking a breath of helium gas and then speaking or singing to the class is a favorite demonstration for an introductory physics course, as it usually elicits appreciative laughter, which serves to energize the class session. Students will usually report that the helium speech "raises the frequency" of the voice. A more accurate description of the…
Robust Speaker Authentication Based on Combined Speech and Voiceprint Recognition
NASA Astrophysics Data System (ADS)
Malcangi, Mario
2009-08-01
Personal authentication is becoming increasingly important in many applications that have to protect proprietary data. Passwords and personal identification numbers (PINs) prove not to be robust enough to ensure that unauthorized people do not use them. Biometric authentication technology may offer a secure, convenient, accurate solution but sometimes fails due to its intrinsically fuzzy nature. This research aims to demonstrate that combining two basic speech processing methods, voiceprint identification and speech recognition, can provide a very high degree of robustness, especially if fuzzy decision logic is used.
Shin, Young Hoon; Seo, Jiwon
2016-01-01
People with hearing or speaking disabilities are deprived of the benefits of conventional speech recognition technology because it is based on acoustic signals. Recent research has focused on silent speech recognition systems that are based on the motions of a speaker’s vocal tract and articulators. Because most silent speech recognition systems use contact sensors that are very inconvenient to users or optical systems that are susceptible to environmental interference, a contactless and robust solution is hence required. Toward this objective, this paper presents a series of signal processing algorithms for a contactless silent speech recognition system using an impulse radio ultra-wide band (IR-UWB) radar. The IR-UWB radar is used to remotely and wirelessly detect motions of the lips and jaw. In order to extract the necessary features of lip and jaw motions from the received radar signals, we propose a feature extraction algorithm. The proposed algorithm noticeably improved speech recognition performance compared to the existing algorithm during our word recognition test with five speakers. We also propose a speech activity detection algorithm to automatically select speech segments from continuous input signals. Thus, speech recognition processing is performed only when speech segments are detected. Our testbed consists of commercial off-the-shelf radar products, and the proposed algorithms are readily applicable without designing specialized radar hardware for silent speech processing. PMID:27801867
Shin, Young Hoon; Seo, Jiwon
2016-10-29
People with hearing or speaking disabilities are deprived of the benefits of conventional speech recognition technology because it is based on acoustic signals. Recent research has focused on silent speech recognition systems that are based on the motions of a speaker's vocal tract and articulators. Because most silent speech recognition systems use contact sensors that are very inconvenient to users or optical systems that are susceptible to environmental interference, a contactless and robust solution is hence required. Toward this objective, this paper presents a series of signal processing algorithms for a contactless silent speech recognition system using an impulse radio ultra-wide band (IR-UWB) radar. The IR-UWB radar is used to remotely and wirelessly detect motions of the lips and jaw. In order to extract the necessary features of lip and jaw motions from the received radar signals, we propose a feature extraction algorithm. The proposed algorithm noticeably improved speech recognition performance compared to the existing algorithm during our word recognition test with five speakers. We also propose a speech activity detection algorithm to automatically select speech segments from continuous input signals. Thus, speech recognition processing is performed only when speech segments are detected. Our testbed consists of commercial off-the-shelf radar products, and the proposed algorithms are readily applicable without designing specialized radar hardware for silent speech processing.
Ahrens, Merle-Marie; Veniero, Domenica; Gross, Joachim; Harvey, Monika; Thut, Gregor
2015-01-01
Many behaviourally relevant sensory events such as motion stimuli and speech have an intrinsic spatio-temporal structure. This will engage intentional and most likely unintentional (automatic) prediction mechanisms enhancing the perception of upcoming stimuli in the event stream. Here we sought to probe the anticipatory processes that are automatically driven by rhythmic input streams in terms of their spatial and temporal components. To this end, we employed an apparent visual motion paradigm testing the effects of pre-target motion on lateralized visual target discrimination. The motion stimuli either moved towards or away from peripheral target positions (valid vs. invalid spatial motion cueing) at a rhythmic or arrhythmic pace (valid vs. invalid temporal motion cueing). Crucially, we emphasized automatic motion-induced anticipatory processes by rendering the motion stimuli non-predictive of upcoming target position (by design) and task-irrelevant (by instruction), and by creating instead endogenous (orthogonal) expectations using symbolic cueing. Our data revealed that the apparent motion cues automatically engaged both spatial and temporal anticipatory processes, but that these processes were dissociated. We further found evidence for lateralisation of anticipatory temporal but not spatial processes. This indicates that distinct mechanisms may drive automatic spatial and temporal extrapolation of upcoming events from rhythmic event streams. This contrasts with previous findings that instead suggest an interaction between spatial and temporal attention processes when endogenously driven. Our results further highlight the need for isolating intentional from unintentional processes for better understanding the various anticipatory mechanisms engaged in processing behaviourally relevant stimuli with predictable spatio-temporal structure such as motion and speech. PMID:26623650
Approximated mutual information training for speech recognition using myoelectric signals.
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.
Intonation and dialog context as constraints for speech recognition.
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.
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.
An experimental version of the MZT (speech-from-text) system with external F(sub 0) control
NASA Astrophysics Data System (ADS)
Nowak, Ignacy
1994-12-01
The version of a Polish speech from text system described in this article was developed using the speech-from-text system. The new system has additional functions which make it possible to enter commands in edited orthographic text to control the phrase component and accentuation parameters. This makes it possible to generate a series of modified intonation contours in the texts spoken by the system. The effects obtained are made easier to control by a graphic illustration of the base frequency pattern in phrases that were last 'spoken' by the system. This version of the system was designed as a test prototype which will help us expand and refine our set of rules for automatic generation of intonation contours, which in turn will enable the fully automated speech-from-text system to generate speech with a more varied and precisely formed fundamental frequency pattern.
The Timing and Effort of Lexical Access in Natural and Degraded Speech
Wagner, Anita E.; Toffanin, Paolo; Başkent, Deniz
2016-01-01
Understanding speech is effortless in ideal situations, and although adverse conditions, such as caused by hearing impairment, often render it an effortful task, they do not necessarily suspend speech comprehension. A prime example of this is speech perception by cochlear implant users, whose hearing prostheses transmit speech as a significantly degraded signal. It is yet unknown how mechanisms of speech processing deal with such degraded signals, and whether they are affected by effortful processing of speech. This paper compares the automatic process of lexical competition between natural and degraded speech, and combines gaze fixations, which capture the course of lexical disambiguation, with pupillometry, which quantifies the mental effort involved in processing speech. Listeners’ ocular responses were recorded during disambiguation of lexical embeddings with matching and mismatching durational cues. Durational cues were selected due to their substantial role in listeners’ quick limitation of the number of lexical candidates for lexical access in natural speech. Results showed that lexical competition increased mental effort in processing natural stimuli in particular in presence of mismatching cues. Signal degradation reduced listeners’ ability to quickly integrate durational cues in lexical selection, and delayed and prolonged lexical competition. The effort of processing degraded speech was increased overall, and because it had its sources at the pre-lexical level this effect can be attributed to listening to degraded speech rather than to lexical disambiguation. In sum, the course of lexical competition was largely comparable for natural and degraded speech, but showed crucial shifts in timing, and different sources of increased mental effort. We argue that well-timed progress of information from sensory to pre-lexical and lexical stages of processing, which is the result of perceptual adaptation during speech development, is the reason why in ideal
Chriskos, Panteleimon; Frantzidis, Christos A; Gkivogkli, Polyxeni T; Bamidis, Panagiotis D; Kourtidou-Papadeli, Chrysoula
2018-01-01
Sleep staging, the process of assigning labels to epochs of sleep, depending on the stage of sleep they belong, is an arduous, time consuming and error prone process as the initial recordings are quite often polluted by noise from different sources. To properly analyze such data and extract clinical knowledge, noise components must be removed or alleviated. In this paper a pre-processing and subsequent sleep staging pipeline for the sleep analysis of electroencephalographic signals is described. Two novel methods of functional connectivity estimation (Synchronization Likelihood/SL and Relative Wavelet Entropy/RWE) are comparatively investigated for automatic sleep staging through manually pre-processed electroencephalographic recordings. A multi-step process that renders signals suitable for further analysis is initially described. Then, two methods that rely on extracting synchronization features from electroencephalographic recordings to achieve computerized sleep staging are proposed, based on bivariate features which provide a functional overview of the brain network, contrary to most proposed methods that rely on extracting univariate time and frequency features. Annotation of sleep epochs is achieved through the presented feature extraction methods by training classifiers, which are in turn able to accurately classify new epochs. Analysis of data from sleep experiments on a randomized, controlled bed-rest study, which was organized by the European Space Agency and was conducted in the "ENVIHAB" facility of the Institute of Aerospace Medicine at the German Aerospace Center (DLR) in Cologne, Germany attains high accuracy rates, over 90% based on ground truth that resulted from manual sleep staging by two experienced sleep experts. Therefore, it can be concluded that the above feature extraction methods are suitable for semi-automatic sleep staging.
Chriskos, Panteleimon; Frantzidis, Christos A.; Gkivogkli, Polyxeni T.; Bamidis, Panagiotis D.; Kourtidou-Papadeli, Chrysoula
2018-01-01
Sleep staging, the process of assigning labels to epochs of sleep, depending on the stage of sleep they belong, is an arduous, time consuming and error prone process as the initial recordings are quite often polluted by noise from different sources. To properly analyze such data and extract clinical knowledge, noise components must be removed or alleviated. In this paper a pre-processing and subsequent sleep staging pipeline for the sleep analysis of electroencephalographic signals is described. Two novel methods of functional connectivity estimation (Synchronization Likelihood/SL and Relative Wavelet Entropy/RWE) are comparatively investigated for automatic sleep staging through manually pre-processed electroencephalographic recordings. A multi-step process that renders signals suitable for further analysis is initially described. Then, two methods that rely on extracting synchronization features from electroencephalographic recordings to achieve computerized sleep staging are proposed, based on bivariate features which provide a functional overview of the brain network, contrary to most proposed methods that rely on extracting univariate time and frequency features. Annotation of sleep epochs is achieved through the presented feature extraction methods by training classifiers, which are in turn able to accurately classify new epochs. Analysis of data from sleep experiments on a randomized, controlled bed-rest study, which was organized by the European Space Agency and was conducted in the “ENVIHAB” facility of the Institute of Aerospace Medicine at the German Aerospace Center (DLR) in Cologne, Germany attains high accuracy rates, over 90% based on ground truth that resulted from manual sleep staging by two experienced sleep experts. Therefore, it can be concluded that the above feature extraction methods are suitable for semi-automatic sleep staging. PMID:29628883
When speaker identity is unavoidable: Neural processing of speaker identity cues in natural speech.
Tuninetti, Alba; Chládková, Kateřina; Peter, Varghese; Schiller, Niels O; Escudero, Paola
2017-11-01
Speech sound acoustic properties vary largely across speakers and accents. When perceiving speech, adult listeners normally disregard non-linguistic variation caused by speaker or accent differences, in order to comprehend the linguistic message, e.g. to correctly identify a speech sound or a word. Here we tested whether the process of normalizing speaker and accent differences, facilitating the recognition of linguistic information, is found at the level of neural processing, and whether it is modulated by the listeners' native language. In a multi-deviant oddball paradigm, native and nonnative speakers of Dutch were exposed to naturally-produced Dutch vowels varying in speaker, sex, accent, and phoneme identity. Unexpectedly, the analysis of mismatch negativity (MMN) amplitudes elicited by each type of change shows a large degree of early perceptual sensitivity to non-linguistic cues. This finding on perception of naturally-produced stimuli contrasts with previous studies examining the perception of synthetic stimuli wherein adult listeners automatically disregard acoustic cues to speaker identity. The present finding bears relevance to speech normalization theories, suggesting that at an unattended level of processing, listeners are indeed sensitive to changes in fundamental frequency in natural speech tokens. Copyright © 2017 Elsevier Inc. All rights reserved.
Intensive Treatment with Ultrasound Visual Feedback for Speech Sound Errors in Childhood Apraxia
Preston, Jonathan L.; Leece, Megan C.; Maas, Edwin
2016-01-01
Ultrasound imaging is an adjunct to traditional speech therapy that has shown to be beneficial in the remediation of speech sound errors. Ultrasound biofeedback can be utilized during therapy to provide clients with additional knowledge about their tongue shapes when attempting to produce sounds that are erroneous. The additional feedback may assist children with childhood apraxia of speech (CAS) in stabilizing motor patterns, thereby facilitating more consistent and accurate productions of sounds and syllables. However, due to its specialized nature, ultrasound visual feedback is a technology that is not widely available to clients. Short-term intensive treatment programs are one option that can be utilized to expand access to ultrasound biofeedback. Schema-based motor learning theory suggests that short-term intensive treatment programs (massed practice) may assist children in acquiring more accurate motor patterns. In this case series, three participants ages 10–14 years diagnosed with CAS attended 16 h of speech therapy over a 2-week period to address residual speech sound errors. Two participants had distortions on rhotic sounds, while the third participant demonstrated lateralization of sibilant sounds. During therapy, cues were provided to assist participants in obtaining a tongue shape that facilitated a correct production of the erred sound. Additional practice without ultrasound was also included. Results suggested that all participants showed signs of acquisition of sounds in error. Generalization and retention results were mixed. One participant showed generalization and retention of sounds that were treated; one showed generalization but limited retention; and the third showed no evidence of generalization or retention. Individual characteristics that may facilitate generalization are discussed. Short-term intensive treatment programs using ultrasound biofeedback may result in the acquisition of more accurate motor patterns and improved articulation
Can blind persons accurately assess body size from the voice?
Pisanski, Katarzyna; Oleszkiewicz, Anna; Sorokowska, Agnieszka
2016-04-01
Vocal tract resonances provide reliable information about a speaker's body size that human listeners use for biosocial judgements as well as speech recognition. Although humans can accurately assess men's relative body size from the voice alone, how this ability is acquired remains unknown. In this study, we test the prediction that accurate voice-based size estimation is possible without prior audiovisual experience linking low frequencies to large bodies. Ninety-one healthy congenitally or early blind, late blind and sighted adults (aged 20-65) participated in the study. On the basis of vowel sounds alone, participants assessed the relative body sizes of male pairs of varying heights. Accuracy of voice-based body size assessments significantly exceeded chance and did not differ among participants who were sighted, or congenitally blind or who had lost their sight later in life. Accuracy increased significantly with relative differences in physical height between men, suggesting that both blind and sighted participants used reliable vocal cues to size (i.e. vocal tract resonances). Our findings demonstrate that prior visual experience is not necessary for accurate body size estimation. This capacity, integral to both nonverbal communication and speech perception, may be present at birth or may generalize from broader cross-modal correspondences. © 2016 The Author(s).
Can blind persons accurately assess body size from the voice?
Oleszkiewicz, Anna; Sorokowska, Agnieszka
2016-01-01
Vocal tract resonances provide reliable information about a speaker's body size that human listeners use for biosocial judgements as well as speech recognition. Although humans can accurately assess men's relative body size from the voice alone, how this ability is acquired remains unknown. In this study, we test the prediction that accurate voice-based size estimation is possible without prior audiovisual experience linking low frequencies to large bodies. Ninety-one healthy congenitally or early blind, late blind and sighted adults (aged 20–65) participated in the study. On the basis of vowel sounds alone, participants assessed the relative body sizes of male pairs of varying heights. Accuracy of voice-based body size assessments significantly exceeded chance and did not differ among participants who were sighted, or congenitally blind or who had lost their sight later in life. Accuracy increased significantly with relative differences in physical height between men, suggesting that both blind and sighted participants used reliable vocal cues to size (i.e. vocal tract resonances). Our findings demonstrate that prior visual experience is not necessary for accurate body size estimation. This capacity, integral to both nonverbal communication and speech perception, may be present at birth or may generalize from broader cross-modal correspondences. PMID:27095264
ERIC Educational Resources Information Center
Gweon, Gahgene; Jain, Mahaveer; McDonough, John; Raj, Bhiksha; Rose, Carolyn P.
2013-01-01
This paper contributes to a theory-grounded methodological foundation for automatic collaborative learning process analysis. It does this by illustrating how insights from the social psychology and sociolinguistics of speech style provide a theoretical framework to inform the design of a computational model. The purpose of that model is to detect…
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.
Crosse, Michael J; Lalor, Edmund C
2014-04-01
Visual speech can greatly enhance a listener's comprehension of auditory speech when they are presented simultaneously. Efforts to determine the neural underpinnings of this phenomenon have been hampered by the limited temporal resolution of hemodynamic imaging and the fact that EEG and magnetoencephalographic data are usually analyzed in response to simple, discrete stimuli. Recent research has shown that neuronal activity in human auditory cortex tracks the envelope of natural speech. Here, we exploit this finding by estimating a linear forward-mapping between the speech envelope and EEG data and show that the latency at which the envelope of natural speech is represented in cortex is shortened by >10 ms when continuous audiovisual speech is presented compared with audio-only speech. In addition, we use a reverse-mapping approach to reconstruct an estimate of the speech stimulus from the EEG data and, by comparing the bimodal estimate with the sum of the unimodal estimates, find no evidence of any nonlinear additive effects in the audiovisual speech condition. These findings point to an underlying mechanism that could account for enhanced comprehension during audiovisual speech. Specifically, we hypothesize that low-level acoustic features that are temporally coherent with the preceding visual stream may be synthesized into a speech object at an earlier latency, which may provide an extended period of low-level processing before extraction of semantic information.
Music and Speech Perception in Children Using Sung Speech
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.
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.
Carroll, Jeff; Zeng, Fan-Gang
2007-01-01
Increasing the number of channels at low frequencies improves discrimination of fundamental frequency (F0) in cochlear implants [Geurts and Wouters 2004]. We conducted three experiments to test whether improved F0 discrimination can be translated into increased speech intelligibility in noise in a cochlear implant simulation. The first experiment measured F0 discrimination and speech intelligibility in quiet as a function of channel density over different frequency regions. The results from this experiment showed a tradeoff in performance between F0 discrimination and speech intelligibility with a limited number of channels. The second experiment tested whether improved F0 discrimination and optimizing this tradeoff could improve speech performance with a competing talker. However, improved F0 discrimination did not improve speech intelligibility in noise. The third experiment identified the critical number of channels needed at low frequencies to improve speech intelligibility in noise. The result showed that, while 16 channels below 500 Hz were needed to observe any improvement in speech intelligibility in noise, even 32 channels did not achieve normal performance. Theoretically, these results suggest that without accurate spectral coding, F0 discrimination and speech perception in noise are two independent processes. Practically, the present results illustrate the need to increase the number of independent channels in cochlear implants. PMID:17604581
Acoustical conditions for speech communication in active elementary school classrooms
NASA Astrophysics Data System (ADS)
Sato, Hiroshi; Bradley, John
2005-04-01
Detailed acoustical measurements were made in 34 active elementary school classrooms with typical rectangular room shape in schools near Ottawa, Canada. There was an average of 21 students in classrooms. The measurements were made to obtain accurate indications of the acoustical quality of conditions for speech communication during actual teaching activities. Mean speech and noise levels were determined from the distribution of recorded sound levels and the average speech-to-noise ratio was 11 dBA. Measured mid-frequency reverberation times (RT) during the same occupied conditions varied from 0.3 to 0.6 s, and were a little less than for the unoccupied rooms. RT values were not related to noise levels. Octave band speech and noise levels, useful-to-detrimental ratios, and Speech Transmission Index values were also determined. Key results included: (1) The average vocal effort of teachers corresponded to louder than Pearsons Raised voice level; (2) teachers increase their voice level to overcome ambient noise; (3) effective speech levels can be enhanced by up to 5 dB by early reflection energy; and (4) student activity is seen to be the dominant noise source, increasing average noise levels by up to 10 dBA during teaching activities. [Work supported by CLLRnet.
The effect of simultaneous text on the recall of noise-degraded speech.
Grossman, Irina; Rajan, Ramesh
2017-05-01
Written and spoken language utilize the same processing system, enabling text to modulate speech processing. We investigated how simultaneously presented text affected speech recall in babble noise using a retrospective recall task. Participants were presented with text-speech sentence pairs in multitalker babble noise and then prompted to recall what they heard or what they read. In Experiment 1, sentence pairs were either congruent or incongruent and they were presented in silence or at 1 of 4 noise levels. Audio and Visual control groups were also tested with sentences presented in only 1 modality. Congruent text facilitated accurate recall of degraded speech; incongruent text had no effect. Text and speech were seldom confused for each other. A consideration of the effects of the language background found that monolingual English speakers outperformed early multilinguals at recalling degraded speech; however the effects of text on speech processing were analogous. Experiment 2 considered if the benefit provided by matching text was maintained when the congruency of the text and speech becomes more ambiguous because of the addition of partially mismatching text-speech sentence pairs that differed only on their final keyword and because of the use of low signal-to-noise ratios. The experiment focused on monolingual English speakers; the results showed that even though participants commonly confused text-for-speech during incongruent text-speech pairings, these confusions could not fully account for the benefit provided by matching text. Thus, we uniquely demonstrate that congruent text benefits the recall of noise-degraded speech. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Automatic intraaortic balloon pump timing using an intrabeat dicrotic notch prediction algorithm.
Schreuder, Jan J; Castiglioni, Alessandro; Donelli, Andrea; Maisano, Francesco; Jansen, Jos R C; Hanania, Ramzi; Hanlon, Pat; Bovelander, Jan; Alfieri, Ottavio
2005-03-01
The efficacy of intraaortic balloon counterpulsation (IABP) during arrhythmic episodes is questionable. A novel algorithm for intrabeat prediction of the dicrotic notch was used for real time IABP inflation timing control. A windkessel model algorithm was used to calculate real-time aortic flow from aortic pressure. The dicrotic notch was predicted using a percentage of calculated peak flow. Automatic inflation timing was set at intrabeat predicted dicrotic notch and was combined with automatic IAB deflation. Prophylactic IABP was applied in 27 patients with low ejection fraction (< 35%) undergoing cardiac surgery. Analysis of IABP at a 1:4 ratio revealed that IAB inflation occurred at a mean of 0.6 +/- 5 ms from the dicrotic notch. In all patients accurate automatic timing at a 1:1 assist ratio was performed. Seventeen patients had episodes of severe arrhythmia, the novel IABP inflation algorithm accurately assisted 318 of 320 arrhythmic beats at a 1:1 ratio. The novel real-time intrabeat IABP inflation timing algorithm performed accurately in all patients during both regular rhythms and severe arrhythmia, allowing fully automatic intrabeat IABP timing.
Speech intelligibility after glossectomy and speech rehabilitation.
Furia, C L; Kowalski, L P; Latorre, M R; Angelis, E C; Martins, N M; Barros, A P; Ribeiro, K C
2001-07-01
Oral tumor resections cause articulation deficiencies, depending on the site, extent of resection, type of reconstruction, and tongue stump mobility. To evaluate the speech intelligibility of patients undergoing total, subtotal, or partial glossectomy, before and after speech therapy. Twenty-seven patients (24 men and 3 women), aged 34 to 77 years (mean age, 56.5 years), underwent glossectomy. Tumor stages were T1 in 3 patients, T2 in 4, T3 in 8, T4 in 11, and TX in 1; node stages, N0 in 15 patients, N1 in 5, N2a-c in 6, and N3 in 1. No patient had metastases (M0). Patients were divided into 3 groups by extent of tongue resection, ie, total (group 1; n = 6), subtotal (group 2; n = 9), and partial (group 3; n = 12). Different phonological tasks were recorded and analyzed by 3 experienced judges, including sustained 7 oral vowels, vowel in a syllable, and the sequence vowel-consonant-vowel (VCV). The intelligibility of spontaneous speech (sequence story) was scored from 1 to 4 in consensus. All patients underwent a therapeutic program to activate articulatory adaptations, compensations, and maximization of the remaining structures for 3 to 6 months. The tasks were recorded after speech therapy. To compare mean changes, analyses of variance and Wilcoxon tests were used. Patients of groups 1 and 2 significantly improved their speech intelligibility (P<.05). Group 1 improved vowels, VCV, and spontaneous speech; group 2, syllable, VCV, and spontaneous speech. Group 3 demonstrated better intelligibility in the pretherapy phase, but the improvement after therapy was not significant. Speech therapy was effective in improving speech intelligibility of patients undergoing glossectomy, even after major resection. Different pretherapy ability between groups was seen, with improvement of speech intelligibility in groups 1 and 2. The improvement of speech intelligibility in group 3 was not statistically significant, possibly because of the small and heterogeneous sample.
Factors that influence the performance of experienced speech recognition users.
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.
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.
Comparison of Classification Methods for Detecting Emotion from Mandarin Speech
NASA Astrophysics Data System (ADS)
Pao, Tsang-Long; Chen, Yu-Te; Yeh, Jun-Heng
It is said that technology comes out from humanity. What is humanity? The very definition of humanity is emotion. Emotion is the basis for all human expression and the underlying theme behind everything that is done, said, thought or imagined. Making computers being able to perceive and respond to human emotion, the human-computer interaction will be more natural. Several classifiers are adopted for automatically assigning an emotion category, such as anger, happiness or sadness, to a speech utterance. These classifiers were designed independently and tested on various emotional speech corpora, making it difficult to compare and evaluate their performance. In this paper, we first compared several popular classification methods and evaluated their performance by applying them to a Mandarin speech corpus consisting of five basic emotions, including anger, happiness, boredom, sadness and neutral. The extracted feature streams contain MFCC, LPCC, and LPC. The experimental results show that the proposed WD-MKNN classifier achieves an accuracy of 81.4% for the 5-class emotion recognition and outperforms other classification techniques, including KNN, MKNN, DW-KNN, LDA, QDA, GMM, HMM, SVM, and BPNN. Then, to verify the advantage of the proposed method, we compared these classifiers by applying them to another Mandarin expressive speech corpus consisting of two emotions. The experimental results still show that the proposed WD-MKNN outperforms others.
User Experience of a Mobile Speaking Application with Automatic Speech Recognition for EFL Learning
ERIC Educational Resources Information Center
Ahn, Tae youn; Lee, Sangmin-Michelle
2016-01-01
With the spread of mobile devices, mobile phones have enormous potential regarding their pedagogical use in language education. The goal of this study is to analyse user experience of a mobile-based learning system that is enhanced by speech recognition technology for the improvement of EFL (English as a foreign language) learners' speaking…
Vogel, Adam P; Block, Susan; Kefalianos, Elaina; Onslow, Mark; Eadie, Patricia; Barth, Ben; Conway, Laura; Mundt, James C; Reilly, Sheena
2015-04-01
To investigate the feasibility of adopting automated interactive voice response (IVR) technology for remotely capturing standardized speech samples from stuttering children. Participants were 10 6-year-old stuttering children. Their parents called a toll-free number from their homes and were prompted to elicit speech from their children using a standard protocol involving conversation, picture description and games. The automated IVR system was implemented using an off-the-shelf telephony software program and delivered by a standard desktop computer. The software infrastructure utilizes voice over internet protocol. Speech samples were automatically recorded during the calls. Video recordings were simultaneously acquired in the home at the time of the call to evaluate the fidelity of the telephone collected samples. Key outcome measures included syllables spoken, percentage of syllables stuttered and an overall rating of stuttering severity using a 10-point scale. Data revealed a high level of relative reliability in terms of intra-class correlation between the video and telephone acquired samples on all outcome measures during the conversation task. Findings were less consistent for speech samples during picture description and games. Results suggest that IVR technology can be used successfully to automate remote capture of child speech samples.
NASA Astrophysics Data System (ADS)
Zhu, Jun; Chen, Lijun; Ma, Lantao; Li, Dejian; Jiang, Wei; Pan, Lihong; Shen, Huiting; Jia, Hongmin; Hsiang, Chingyun; Cheng, Guojie; Ling, Li; Chen, Shijie; Wang, Jun; Liao, Wenkui; Zhang, Gary
2014-04-01
Defect review is a time consuming job. Human error makes result inconsistent. The defects located on don't care area would not hurt the yield and no need to review them such as defects on dark area. However, critical area defects can impact yield dramatically and need more attention to review them such as defects on clear area. With decrease in integrated circuit dimensions, mask defects are always thousands detected during inspection even more. Traditional manual or simple classification approaches are unable to meet efficient and accuracy requirement. This paper focuses on automatic defect management and classification solution using image output of Lasertec inspection equipment and Anchor pattern centric image process technology. The number of mask defect found during an inspection is always in the range of thousands or even more. This system can handle large number defects with quick and accurate defect classification result. Our experiment includes Die to Die and Single Die modes. The classification accuracy can reach 87.4% and 93.3%. No critical or printable defects are missing in our test cases. The missing classification defects are 0.25% and 0.24% in Die to Die mode and Single Die mode. This kind of missing rate is encouraging and acceptable to apply on production line. The result can be output and reloaded back to inspection machine to have further review. This step helps users to validate some unsure defects with clear and magnification images when captured images can't provide enough information to make judgment. This system effectively reduces expensive inline defect review time. As a fully inline automated defect management solution, the system could be compatible with current inspection approach and integrated with optical simulation even scoring function and guide wafer level defect inspection.
NASA Astrophysics Data System (ADS)
Plata, Jose J.; Nath, Pinku; Usanmaz, Demet; Carrete, Jesús; Toher, Cormac; de Jong, Maarten; Asta, Mark; Fornari, Marco; Nardelli, Marco Buongiorno; Curtarolo, Stefano
2017-10-01
One of the most accurate approaches for calculating lattice thermal conductivity, , is solving the Boltzmann transport equation starting from third-order anharmonic force constants. In addition to the underlying approximations of ab-initio parameterization, two main challenges are associated with this path: high computational costs and lack of automation in the frameworks using this methodology, which affect the discovery rate of novel materials with ad-hoc properties. Here, the Automatic Anharmonic Phonon Library (AAPL) is presented. It efficiently computes interatomic force constants by making effective use of crystal symmetry analysis, it solves the Boltzmann transport equation to obtain , and allows a fully integrated operation with minimum user intervention, a rational addition to the current high-throughput accelerated materials development framework AFLOW. An "experiment vs. theory" study of the approach is shown, comparing accuracy and speed with respect to other available packages, and for materials characterized by strong electron localization and correlation. Combining AAPL with the pseudo-hybrid functional ACBN0 is possible to improve accuracy without increasing computational requirements.
The Development of the Speaker Independent ARM Continuous Speech Recognition System
1992-01-01
spokeTi airborne reconnaissance reports u-ing a speech recognition system based on phoneme-level hidden Markov models (HMMs). Previous versions of the ARM...will involve automatic selection from multiple model sets, corresponding to different speaker types, and that the most rudimen- tary partition of a...The vocabulary size for the ARM task is 497 words. These words are related to the phoneme-level symbols corresponding to the models in the model set
Intra-oral pressure-based voicing control of electrolaryngeal speech with intra-oral vibrator.
Takahashi, Hirokazu; Nakao, Masayuki; Kikuchi, Yataro; Kaga, Kimitaka
2008-07-01
In normal speech, coordinated activities of intrinsic laryngeal muscles suspend a glottal sound at utterance of voiceless consonants, automatically realizing a voicing control. In electrolaryngeal speech, however, the lack of voicing control is one of the causes of unclear voice, voiceless consonants tending to be misheard as the corresponding voiced consonants. In the present work, we developed an intra-oral vibrator with an intra-oral pressure sensor that detected utterance of voiceless phonemes during the intra-oral electrolaryngeal speech, and demonstrated that an intra-oral pressure-based voicing control could improve the intelligibility of the speech. The test voices were obtained from one electrolaryngeal speaker and one normal speaker. We first investigated on the speech analysis software how a voice onset time (VOT) and first formant (F1) transition of the test consonant-vowel syllables contributed to voiceless/voiced contrasts, and developed an adequate voicing control strategy. We then compared the intelligibility of consonant-vowel syllables among the intra-oral electrolaryngeal speech with and without online voicing control. The increase of intra-oral pressure, typically with a peak ranging from 10 to 50 gf/cm2, could reliably identify utterance of voiceless consonants. The speech analysis and intelligibility test then demonstrated that a short VOT caused the misidentification of the voiced consonants due to a clear F1 transition. Finally, taking these results together, the online voicing control, which suspended the prosthetic tone while the intra-oral pressure exceeded 2.5 gf/cm2 and during the 35 milliseconds that followed, proved efficient to improve the voiceless/voiced contrast.
Musical expertise and foreign speech perception.
Martínez-Montes, Eduardo; Hernández-Pérez, Heivet; Chobert, Julie; Morgado-Rodríguez, Lisbet; Suárez-Murias, Carlos; Valdés-Sosa, Pedro A; Besson, Mireille
2013-01-01
The aim of this experiment was to investigate the influence of musical expertise on the automatic perception of foreign syllables and harmonic sounds. Participants were Cuban students with high level of expertise in music or in visual arts and with the same level of general education and socio-economic background. We used a multi-feature Mismatch Negativity (MMN) design with sequences of either syllables in Mandarin Chinese or harmonic sounds, both comprising deviants in pitch contour, duration and Voice Onset Time (VOT) or equivalent that were either far from (Large deviants) or close to (Small deviants) the standard. For both Mandarin syllables and harmonic sounds, results were clear-cut in showing larger MMNs to pitch contour deviants in musicians than in visual artists. Results were less clear for duration and VOT deviants, possibly because of the specific characteristics of the stimuli. Results are interpreted as reflecting similar processing of pitch contour in speech and non-speech sounds. The implications of these results for understanding the influence of intense musical training from childhood to adulthood and of genetic predispositions for music on foreign language perception are discussed.
Musical expertise and foreign speech perception
Martínez-Montes, Eduardo; Hernández-Pérez, Heivet; Chobert, Julie; Morgado-Rodríguez, Lisbet; Suárez-Murias, Carlos; Valdés-Sosa, Pedro A.; Besson, Mireille
2013-01-01
The aim of this experiment was to investigate the influence of musical expertise on the automatic perception of foreign syllables and harmonic sounds. Participants were Cuban students with high level of expertise in music or in visual arts and with the same level of general education and socio-economic background. We used a multi-feature Mismatch Negativity (MMN) design with sequences of either syllables in Mandarin Chinese or harmonic sounds, both comprising deviants in pitch contour, duration and Voice Onset Time (VOT) or equivalent that were either far from (Large deviants) or close to (Small deviants) the standard. For both Mandarin syllables and harmonic sounds, results were clear-cut in showing larger MMNs to pitch contour deviants in musicians than in visual artists. Results were less clear for duration and VOT deviants, possibly because of the specific characteristics of the stimuli. Results are interpreted as reflecting similar processing of pitch contour in speech and non-speech sounds. The implications of these results for understanding the influence of intense musical training from childhood to adulthood and of genetic predispositions for music on foreign language perception are discussed. PMID:24294193
ERIC Educational Resources Information Center
Franco, Horacio; Bratt, Harry; Rossier, Romain; Rao Gadde, Venkata; Shriberg, Elizabeth; Abrash, Victor; Precoda, Kristin
2010-01-01
SRI International's EduSpeak[R] system is a software development toolkit that enables developers of interactive language education software to use state-of-the-art speech recognition and pronunciation scoring technology. Automatic pronunciation scoring allows the computer to provide feedback on the overall quality of pronunciation and to point to…
Development of an Automatic Differentiation Version of the FPX Rotor Code
NASA Technical Reports Server (NTRS)
Hu, Hong
1996-01-01
The ADIFOR2.0 automatic differentiator is applied to the FPX rotor code along with the grid generator GRGN3. The FPX is an eXtended Full-Potential CFD code for rotor calculations. The automatic differentiation version of the code is obtained, which provides both non-geometry and geometry sensitivity derivatives. The sensitivity derivatives via automatic differentiation are presented and compared with divided difference generated derivatives. The study shows that automatic differentiation method gives accurate derivative values in an efficient manner.
Centanni, Tracy M.; Chen, Fuyi; Booker, Anne M.; Engineer, Crystal T.; Sloan, Andrew M.; Rennaker, Robert L.; LoTurco, Joseph J.; Kilgard, Michael P.
2014-01-01
In utero RNAi of the dyslexia-associated gene Kiaa0319 in rats (KIA-) degrades cortical responses to speech sounds and increases trial-by-trial variability in onset latency. We tested the hypothesis that KIA- rats would be impaired at speech sound discrimination. KIA- rats needed twice as much training in quiet conditions to perform at control levels and remained impaired at several speech tasks. Focused training using truncated speech sounds was able to normalize speech discrimination in quiet and background noise conditions. Training also normalized trial-by-trial neural variability and temporal phase locking. Cortical activity from speech trained KIA- rats was sufficient to accurately discriminate between similar consonant sounds. These results provide the first direct evidence that assumed reduced expression of the dyslexia-associated gene KIAA0319 can cause phoneme processing impairments similar to those seen in dyslexia and that intensive behavioral therapy can eliminate these impairments. PMID:24871331
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.
The development of visual speech perception in Mandarin Chinese-speaking children.
Chen, Liang; Lei, Jianghua
2017-01-01
The present study aimed to investigate the development of visual speech perception in Chinese-speaking children. Children aged 7, 13 and 16 were asked to visually identify both consonant and vowel sounds in Chinese as quickly and accurately as possible. Results revealed (1) an increase in accuracy of visual speech perception between ages 7 and 13 after which the accuracy rate either stagnates or drops; and (2) a U-shaped development pattern in speed of perception with peak performance in 13-year olds. Results also showed that across all age groups, the overall levels of accuracy rose, whereas the response times fell for simplex finals, complex finals and initials. These findings suggest that (1) visual speech perception in Chinese is a developmental process that is acquired over time and is still fine-tuned well into late adolescence; (2) factors other than cross-linguistic differences in phonological complexity and degrees of reliance on visual information are involved in development of visual speech perception.
Wu, Hongjun; Wang, Bingjian; Zhu, Xinpu; Chu, Guang; Zhang, Zhi
2016-08-01
The widely used oscillometric automated blood pressure (BP) monitor was continuously questioned on its accuracy. A novel BP kit named Accutension which adopted Korotkoff auscultation method was then devised. Accutension worked with a miniature microphone, a pressure sensor, and a smartphone. The BP values were automatically displayed on the smartphone screen through the installed App. Data recorded in the phone could be played back and reconfirmed after measurement. They could also be uploaded and saved to the iCloud. The accuracy and consistency of this novel electronic auscultatory sphygmomanometer was preliminarily verified here. Thirty-two subjects were included and 82 qualified readings were obtained. The mean differences ± SD for systolic and diastolic BP readings between Accutension and mercury sphygmomanometer were 0.87 ± 2.86 and -0.94 ± 2.93 mm Hg. Agreements between Accutension and mercury sphygmomanometer were highly significant for systolic (ICC = 0.993, 95% confidence interval (CI): 0.989-0.995) and diastolic (ICC = 0.987, 95% CI: 0.979-0.991). In conclusion, Accutension worked accurately based on our pilot study data. The difference was acceptable. ICC and Bland-Altman plot charts showed good agreements with manual measurements. Systolic readings of Accutension were slightly higher than those of manual measurement, while diastolic readings were slightly lower. One possible reason was that Accutension captured the first and the last korotkoff sound more sensitively than human ear during manual measurement and avoided sound missing, so that it might be more accurate than traditional mercury sphygmomanometer. By documenting and analyzing of variant tendency of BP values, Accutension helps management of hypertension and therefore contributes to the mobile heath service.
Shao, Xu; Milner, Ben
2005-08-01
This work proposes a method to reconstruct an acoustic speech signal solely from a stream of mel-frequency cepstral coefficients (MFCCs) as may be encountered in a distributed speech recognition (DSR) system. Previous methods for speech reconstruction have required, in addition to the MFCC vectors, fundamental frequency and voicing components. In this work the voicing classification and fundamental frequency are predicted from the MFCC vectors themselves using two maximum a posteriori (MAP) methods. The first method enables fundamental frequency prediction by modeling the joint density of MFCCs and fundamental frequency using a single Gaussian mixture model (GMM). The second scheme uses a set of hidden Markov models (HMMs) to link together a set of state-dependent GMMs, which enables a more localized modeling of the joint density of MFCCs and fundamental frequency. Experimental results on speaker-independent male and female speech show that accurate voicing classification and fundamental frequency prediction is attained when compared to hand-corrected reference fundamental frequency measurements. The use of the predicted fundamental frequency and voicing for speech reconstruction is shown to give very similar speech quality to that obtained using the reference fundamental frequency and voicing.
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.
Automatic River Network Extraction from LIDAR Data
NASA Astrophysics Data System (ADS)
Maderal, E. N.; Valcarcel, N.; Delgado, J.; Sevilla, C.; Ojeda, J. C.
2016-06-01
National Geographic Institute of Spain (IGN-ES) has launched a new production system for automatic river network extraction for the Geospatial Reference Information (GRI) within hydrography theme. The goal is to get an accurate and updated river network, automatically extracted as possible. For this, IGN-ES has full LiDAR coverage for the whole Spanish territory with a density of 0.5 points per square meter. To implement this work, it has been validated the technical feasibility, developed a methodology to automate each production phase: hydrological terrain models generation with 2 meter grid size and river network extraction combining hydrographic criteria (topographic network) and hydrological criteria (flow accumulation river network), and finally the production was launched. The key points of this work has been managing a big data environment, more than 160,000 Lidar data files, the infrastructure to store (up to 40 Tb between results and intermediate files), and process; using local virtualization and the Amazon Web Service (AWS), which allowed to obtain this automatic production within 6 months, it also has been important the software stability (TerraScan-TerraSolid, GlobalMapper-Blue Marble , FME-Safe, ArcGIS-Esri) and finally, the human resources managing. The results of this production has been an accurate automatic river network extraction for the whole country with a significant improvement for the altimetric component of the 3D linear vector. This article presents the technical feasibility, the production methodology, the automatic river network extraction production and its advantages over traditional vector extraction systems.
Talker identification across source mechanisms: experiments with laryngeal and electrolarynx speech.
Perrachione, Tyler K; Stepp, Cara E; Hillman, Robert E; Wong, Patrick C M
2014-10-01
The purpose of this study was to determine listeners' ability to learn talker identity from speech produced with an electrolarynx, explore source and filter differentiation in talker identification, and describe acoustic-phonetic changes associated with electrolarynx use. Healthy adult control listeners learned to identify talkers from speech recordings produced using talkers' normal laryngeal vocal source or an electrolarynx. Listeners' abilities to identify talkers from the trained vocal source (Experiment 1) and generalize this knowledge to the untrained source (Experiment 2) were assessed. Acoustic-phonetic measurements of spectral differences between source mechanisms were performed. Additional listeners attempted to match recordings from different source mechanisms to a single talker (Experiment 3). Listeners successfully learned talker identity from electrolarynx speech but less accurately than from laryngeal speech. Listeners were unable to generalize talker identity to the untrained source mechanism. Electrolarynx use resulted in vowels with higher F1 frequencies compared with laryngeal speech. Listeners matched recordings from different sources to a single talker better than chance. Electrolarynx speech, although lacking individual differences in voice quality, nevertheless conveys sufficient indexical information related to the vocal filter and articulation for listeners to identify individual talkers. Psychologically, perception of talker identity arises from a "gestalt" of the vocal source and filter.
Talker identification across source mechanisms: Experiments with laryngeal and electrolarynx speech
Perrachione, Tyler K.; Stepp, Cara E.; Hillman, Robert E.; Wong, Patrick C.M.
2015-01-01
Purpose To determine listeners' ability to learn talker identity from speech produced with an electrolarynx, explore source and filter differentiation in talker identification, and describe acoustic-phonetic changes associated with electrolarynx use. Method Healthy adult control listeners learned to identify talkers from speech recordings produced using talkers' normal laryngeal vocal source or an electrolarynx. Listeners' abilities to identify talkers from the trained vocal source (Experiment 1) and generalize this knowledge to the untrained source (Experiment 2) were assessed. Acoustic-phonetic measurements of spectral differences between source mechanisms were performed. Additional listeners attempted to match recordings from different source mechanisms to a single talker (Experiment 3). Results Listeners successfully learned talker identity from electrolarynx speech, but less accurately than from laryngeal speech. Listeners were unable to generalize talker identity to the untrained source mechanism. Electrolarynx use resulted in vowels with higher F1 frequencies compared to laryngeal speech. Listeners matched recordings from different sources to a single talker better than chance. Conclusions Electrolarynx speech, though lacking individual differences in voice quality, nevertheless conveys sufficient indexical information related to the vocal filter and articulation for listeners to identify individual talkers. Psychologically, perception of talker identity arises from a “gestalt” of the vocal source and filter. PMID:24801962
Helium Speech: An Application of Standing Waves
NASA Astrophysics Data System (ADS)
Wentworth, Christopher D.
2011-04-01
Taking a breath of helium gas and then speaking or singing to the class is a favorite demonstration for an introductory physics course, as it usually elicits appreciative laughter, which serves to energize the class session. Students will usually report that the helium speech "raises the frequency" of the voice. A more accurate description of the phenomenon requires that we distinguish between the frequencies of sound produced by the larynx and the filtering of those frequencies by the vocal tract. We will describe here an experiment done by introductory physics students that uses helium speech as a context for learning about the human vocal system and as an application of the standing sound-wave concept. Modern acoustic analysis software easily obtained by instructors for student use allows data to be obtained and analyzed quickly.
Davidow, Jason H; Grossman, Heather L; Edge, Robin L
2018-05-01
Voluntary stuttering techniques involve persons who stutter purposefully interjecting disfluencies into their speech. Little research has been conducted on the impact of these techniques on the speech pattern of persons who stutter. The present study examined whether changes in the frequency of voluntary stuttering accompanied changes in stuttering frequency, articulation rate, speech naturalness, and speech effort. In total, 12 persons who stutter aged 16-34 years participated. Participants read four 300-syllable passages during a control condition, and three voluntary stuttering conditions that involved attempting to produce purposeful, tension-free repetitions of initial sounds or syllables of a word for two or more repetitions (i.e., bouncing). The three voluntary stuttering conditions included bouncing on 5%, 10%, and 15% of syllables read. Friedman tests and follow-up Wilcoxon signed ranks tests were conducted for the statistical analyses. Stuttering frequency, articulation rate, and speech naturalness were significantly different between the voluntary stuttering conditions. Speech effort did not differ between the voluntary stuttering conditions. Stuttering frequency was significantly lower during the three voluntary stuttering conditions compared to the control condition, and speech effort was significantly lower during two of the three voluntary stuttering conditions compared to the control condition. Due to changes in articulation rate across the voluntary stuttering conditions, it is difficult to conclude, as has been suggested previously, that voluntary stuttering is the reason for stuttering reductions found when using voluntary stuttering techniques. Additionally, future investigations should examine different types of voluntary stuttering over an extended period of time to determine their impact on stuttering frequency, speech rate, speech naturalness, and speech effort.
Comprehension of synthetic speech and digitized natural speech by adults with aphasia.
Hux, Karen; Knollman-Porter, Kelly; Brown, Jessica; Wallace, Sarah E
2017-09-01
Using text-to-speech technology to provide simultaneous written and auditory content presentation may help compensate for chronic reading challenges if people with aphasia can understand synthetic speech output; however, inherent auditory comprehension challenges experienced by people with aphasia may make understanding synthetic speech difficult. This study's purpose was to compare the preferences and auditory comprehension accuracy of people with aphasia when listening to sentences generated with digitized natural speech, Alex synthetic speech (i.e., Macintosh platform), or David synthetic speech (i.e., Windows platform). The methodology required each of 20 participants with aphasia to select one of four images corresponding in meaning to each of 60 sentences comprising three stimulus sets. Results revealed significantly better accuracy given digitized natural speech than either synthetic speech option; however, individual participant performance analyses revealed three patterns: (a) comparable accuracy regardless of speech condition for 30% of participants, (b) comparable accuracy between digitized natural speech and one, but not both, synthetic speech option for 45% of participants, and (c) greater accuracy with digitized natural speech than with either synthetic speech option for remaining participants. Ranking and Likert-scale rating data revealed a preference for digitized natural speech and David synthetic speech over Alex synthetic speech. Results suggest many individuals with aphasia can comprehend synthetic speech options available on popular operating systems. Further examination of synthetic speech use to support reading comprehension through text-to-speech technology is thus warranted. Copyright © 2017 Elsevier Inc. All rights reserved.
Auditory Perceptual Learning for Speech Perception Can be Enhanced by Audiovisual Training.
Bernstein, Lynne E; Auer, Edward T; Eberhardt, Silvio P; Jiang, Jintao
2013-01-01
Speech perception under audiovisual (AV) conditions is well known to confer benefits to perception such as increased speed and accuracy. Here, we investigated how AV training might benefit or impede auditory perceptual learning of speech degraded by vocoding. In Experiments 1 and 3, participants learned paired associations between vocoded spoken nonsense words and nonsense pictures. In Experiment 1, paired-associates (PA) AV training of one group of participants was compared with audio-only (AO) training of another group. When tested under AO conditions, the AV-trained group was significantly more accurate than the AO-trained group. In addition, pre- and post-training AO forced-choice consonant identification with untrained nonsense words showed that AV-trained participants had learned significantly more than AO participants. The pattern of results pointed to their having learned at the level of the auditory phonetic features of the vocoded stimuli. Experiment 2, a no-training control with testing and re-testing on the AO consonant identification, showed that the controls were as accurate as the AO-trained participants in Experiment 1 but less accurate than the AV-trained participants. In Experiment 3, PA training alternated AV and AO conditions on a list-by-list basis within participants, and training was to criterion (92% correct). PA training with AO stimuli was reliably more effective than training with AV stimuli. We explain these discrepant results in terms of the so-called "reverse hierarchy theory" of perceptual learning and in terms of the diverse multisensory and unisensory processing resources available to speech perception. We propose that early AV speech integration can potentially impede auditory perceptual learning; but visual top-down access to relevant auditory features can promote auditory perceptual learning.
Auditory Perceptual Learning for Speech Perception Can be Enhanced by Audiovisual Training
Bernstein, Lynne E.; Auer, Edward T.; Eberhardt, Silvio P.; Jiang, Jintao
2013-01-01
Speech perception under audiovisual (AV) conditions is well known to confer benefits to perception such as increased speed and accuracy. Here, we investigated how AV training might benefit or impede auditory perceptual learning of speech degraded by vocoding. In Experiments 1 and 3, participants learned paired associations between vocoded spoken nonsense words and nonsense pictures. In Experiment 1, paired-associates (PA) AV training of one group of participants was compared with audio-only (AO) training of another group. When tested under AO conditions, the AV-trained group was significantly more accurate than the AO-trained group. In addition, pre- and post-training AO forced-choice consonant identification with untrained nonsense words showed that AV-trained participants had learned significantly more than AO participants. The pattern of results pointed to their having learned at the level of the auditory phonetic features of the vocoded stimuli. Experiment 2, a no-training control with testing and re-testing on the AO consonant identification, showed that the controls were as accurate as the AO-trained participants in Experiment 1 but less accurate than the AV-trained participants. In Experiment 3, PA training alternated AV and AO conditions on a list-by-list basis within participants, and training was to criterion (92% correct). PA training with AO stimuli was reliably more effective than training with AV stimuli. We explain these discrepant results in terms of the so-called “reverse hierarchy theory” of perceptual learning and in terms of the diverse multisensory and unisensory processing resources available to speech perception. We propose that early AV speech integration can potentially impede auditory perceptual learning; but visual top-down access to relevant auditory features can promote auditory perceptual learning. PMID:23515520
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.
Automatic Classification of Question & Answer Discourse Segments from Teacher's Speech in Classrooms
ERIC Educational Resources Information Center
Blanchard, Nathaniel; D'Mello, Sidney; Olney, Andrew M.; Nystrand, Martin
2015-01-01
Question-answer (Q&A) is fundamental for dialogic instruction, an important pedagogical technique based on the free exchange of ideas and open-ended discussion. Automatically detecting Q&A is key to providing teachers with feedback on appropriate use of dialogic instructional strategies. In line with this, this paper studies the…
Speech-to-Speech Relay Service
... are specifically trained in understanding a variety of speech disorders, which enables them to repeat what the caller says in a manner that makes the caller’s words clear and understandable to the ... people with speech disabilities cannot communicate by telephone because the parties ...
Musical melody and speech intonation: singing a different tune.
Zatorre, Robert J; Baum, Shari R
2012-01-01
Music and speech are often cited as characteristically human forms of communication. Both share the features of hierarchical structure, complex sound systems, and sensorimotor sequencing demands, and both are used to convey and influence emotions, among other functions [1]. Both music and speech also prominently use acoustical frequency modulations, perceived as variations in pitch, as part of their communicative repertoire. Given these similarities, and the fact that pitch perception and production involve the same peripheral transduction system (cochlea) and the same production mechanism (vocal tract), it might be natural to assume that pitch processing in speech and music would also depend on the same underlying cognitive and neural mechanisms. In this essay we argue that the processing of pitch information differs significantly for speech and music; specifically, we suggest that there are two pitch-related processing systems, one for more coarse-grained, approximate analysis and one for more fine-grained accurate representation, and that the latter is unique to music. More broadly, this dissociation offers clues about the interface between sensory and motor systems, and highlights the idea that multiple processing streams are a ubiquitous feature of neuro-cognitive architectures.
Rumbach, Anna F; Rose, Tanya A; Cheah, Mynn
2018-01-29
To explore Australian speech-language pathologists' use of non-speech oral motor exercises, and rationales for using/not using non-speech oral motor exercises in clinical practice. A total of 124 speech-language pathologists practising in Australia, working with paediatric and/or adult clients with speech sound difficulties, completed an online survey. The majority of speech-language pathologists reported that they did not use non-speech oral motor exercises when working with paediatric or adult clients with speech sound difficulties. However, more than half of the speech-language pathologists working with adult clients who have dysarthria reported using non-speech oral motor exercises with this population. The most frequently reported rationale for using non-speech oral motor exercises in speech sound difficulty management was to improve awareness/placement of articulators. The majority of speech-language pathologists agreed there is no clear clinical or research evidence base to support non-speech oral motor exercise use with clients who have speech sound difficulties. This study provides an overview of Australian speech-language pathologists' reported use and perceptions of non-speech oral motor exercises' applicability and efficacy in treating paediatric and adult clients who have speech sound difficulties. The research findings provide speech-language pathologists with insight into how and why non-speech oral motor exercises are currently used, and adds to the knowledge base regarding Australian speech-language pathology practice of non-speech oral motor exercises in the treatment of speech sound difficulties. Implications for Rehabilitation Non-speech oral motor exercises refer to oral motor activities which do not involve speech, but involve the manipulation or stimulation of oral structures including the lips, tongue, jaw, and soft palate. Non-speech oral motor exercises are intended to improve the function (e.g., movement, strength) of oral structures. The
An accurate method of extracting fat droplets in liver images for quantitative evaluation
NASA Astrophysics Data System (ADS)
Ishikawa, Masahiro; Kobayashi, Naoki; Komagata, Hideki; Shinoda, Kazuma; Yamaguchi, Masahiro; Abe, Tokiya; Hashiguchi, Akinori; Sakamoto, Michiie
2015-03-01
The steatosis in liver pathological tissue images is a promising indicator of nonalcoholic fatty liver disease (NAFLD) and the possible risk of hepatocellular carcinoma (HCC). The resulting values are also important for ensuring the automatic and accurate classification of HCC images, because the existence of many fat droplets is likely to create errors in quantifying the morphological features used in the process. In this study we propose a method that can automatically detect, and exclude regions with many fat droplets by using the feature values of colors, shapes and the arrangement of cell nuclei. We implement the method and confirm that it can accurately detect fat droplets and quantify the fat droplet ratio of actual images. This investigation also clarifies the effective characteristics that contribute to accurate detection.
Co-speech iconic gestures and visuo-spatial working memory.
Wu, Ying Choon; Coulson, Seana
2014-11-01
Three experiments tested the role of verbal versus visuo-spatial working memory in the comprehension of co-speech iconic gestures. In Experiment 1, participants viewed congruent discourse primes in which the speaker's gestures matched the information conveyed by his speech, and incongruent ones in which the semantic content of the speaker's gestures diverged from that in his speech. Discourse primes were followed by picture probes that participants judged as being either related or unrelated to the preceding clip. Performance on this picture probe classification task was faster and more accurate after congruent than incongruent discourse primes. The effect of discourse congruency on response times was linearly related to measures of visuo-spatial, but not verbal, working memory capacity, as participants with greater visuo-spatial WM capacity benefited more from congruent gestures. In Experiments 2 and 3, participants performed the same picture probe classification task under conditions of high and low loads on concurrent visuo-spatial (Experiment 2) and verbal (Experiment 3) memory tasks. Effects of discourse congruency and verbal WM load were additive, while effects of discourse congruency and visuo-spatial WM load were interactive. Results suggest that congruent co-speech gestures facilitate multi-modal language comprehension, and indicate an important role for visuo-spatial WM in these speech-gesture integration processes. Copyright © 2014 Elsevier B.V. All rights reserved.
Articulatory speech synthesis and speech production modelling
NASA Astrophysics Data System (ADS)
Huang, Jun
This dissertation addresses the problem of speech synthesis and speech production modelling based on the fundamental principles of human speech production. Unlike the conventional source-filter model, which assumes the independence of the excitation and the acoustic filter, we treat the entire vocal apparatus as one system consisting of a fluid dynamic aspect and a mechanical part. We model the vocal tract by a three-dimensional moving geometry. We also model the sound propagation inside the vocal apparatus as a three-dimensional nonplane-wave propagation inside a viscous fluid described by Navier-Stokes equations. In our work, we first propose a combined minimum energy and minimum jerk criterion to estimate the dynamic vocal tract movements during speech production. Both theoretical error bound analysis and experimental results show that this method can achieve very close match at the target points and avoid the abrupt change in articulatory trajectory at the same time. Second, a mechanical vocal fold model is used to compute the excitation signal of the vocal tract. The advantage of this model is that it is closely coupled with the vocal tract system based on fundamental aerodynamics. As a result, we can obtain an excitation signal with much more detail than the conventional parametric vocal fold excitation model. Furthermore, strong evidence of source-tract interaction is observed. Finally, we propose a computational model of the fricative and stop types of sounds based on the physical principles of speech production. The advantage of this model is that it uses an exogenous process to model the additional nonsteady and nonlinear effects due to the flow mode, which are ignored by the conventional source- filter speech production model. A recursive algorithm is used to estimate the model parameters. Experimental results show that this model is able to synthesize good quality fricative and stop types of sounds. Based on our dissertation work, we carefully argue
Study of wavelet packet energy entropy for emotion classification in speech and glottal signals
NASA Astrophysics Data System (ADS)
He, Ling; Lech, Margaret; Zhang, Jing; Ren, Xiaomei; Deng, Lihua
2013-07-01
The automatic speech emotion recognition has important applications in human-machine communication. Majority of current research in this area is focused on finding optimal feature parameters. In recent studies, several glottal features were examined as potential cues for emotion differentiation. In this study, a new type of feature parameter is proposed, which calculates energy entropy on values within selected Wavelet Packet frequency bands. The modeling and classification tasks are conducted using the classical GMM algorithm. The experiments use two data sets: the Speech Under Simulated Emotion (SUSE) data set annotated with three different emotions (angry, neutral and soft) and Berlin Emotional Speech (BES) database annotated with seven different emotions (angry, bored, disgust, fear, happy, sad and neutral). The average classification accuracy achieved for the SUSE data (74%-76%) is significantly higher than the accuracy achieved for the BES data (51%-54%). In both cases, the accuracy was significantly higher than the respective random guessing levels (33% for SUSE and 14.3% for BES).
[Improving speech comprehension using a new cochlear implant speech processor].
Müller-Deile, J; Kortmann, T; Hoppe, U; Hessel, H; Morsnowski, A
2009-06-01
The aim of this multicenter clinical field study was to assess the benefits of the new Freedom 24 sound processor for cochlear implant (CI) users implanted with the Nucleus 24 cochlear implant system. The study included 48 postlingually profoundly deaf experienced CI users who demonstrated speech comprehension performance with their current speech processor on the Oldenburg sentence test (OLSA) in quiet conditions of at least 80% correct scores and who were able to perform adaptive speech threshold testing using the OLSA in noisy conditions. Following baseline measures of speech comprehension performance with their current speech processor, subjects were upgraded to the Freedom 24 speech processor. After a take-home trial period of at least 2 weeks, subject performance was evaluated by measuring the speech reception threshold with the Freiburg multisyllabic word test and speech intelligibility with the Freiburg monosyllabic word test at 50 dB and 70 dB in the sound field. The results demonstrated highly significant benefits for speech comprehension with the new speech processor. Significant benefits for speech comprehension were also demonstrated with the new speech processor when tested in competing background noise.In contrast, use of the Abbreviated Profile of Hearing Aid Benefit (APHAB) did not prove to be a suitably sensitive assessment tool for comparative subjective self-assessment of hearing benefits with each processor. Use of the preprocessing algorithm known as adaptive dynamic range optimization (ADRO) in the Freedom 24 led to additional improvements over the standard upgrade map for speech comprehension in quiet and showed equivalent performance in noise. Through use of the preprocessing beam-forming algorithm BEAM, subjects demonstrated a highly significant improved signal-to-noise ratio for speech comprehension thresholds (i.e., signal-to-noise ratio for 50% speech comprehension scores) when tested with an adaptive procedure using the Oldenburg
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ravishankar, C., Hughes Network Systems, Germantown, MD
Speech is the predominant means of communication between human beings and since the invention of the telephone by Alexander Graham Bell in 1876, speech services have remained to be the core service in almost all telecommunication systems. Original analog methods of telephony had the disadvantage of speech signal getting corrupted by noise, cross-talk and distortion Long haul transmissions which use repeaters to compensate for the loss in signal strength on transmission links also increase the associated noise and distortion. On the other hand digital transmission is relatively immune to noise, cross-talk and distortion primarily because of the capability to faithfullymore » regenerate digital signal at each repeater purely based on a binary decision. Hence end-to-end performance of the digital link essentially becomes independent of the length and operating frequency bands of the link Hence from a transmission point of view digital transmission has been the preferred approach due to its higher immunity to noise. The need to carry digital speech became extremely important from a service provision point of view as well. Modem requirements have introduced the need for robust, flexible and secure services that can carry a multitude of signal types (such as voice, data and video) without a fundamental change in infrastructure. Such a requirement could not have been easily met without the advent of digital transmission systems, thereby requiring speech to be coded digitally. The term Speech Coding is often referred to techniques that represent or code speech signals either directly as a waveform or as a set of parameters by analyzing the speech signal. In either case, the codes are transmitted to the distant end where speech is reconstructed or synthesized using the received set of codes. A more generic term that is applicable to these techniques that is often interchangeably used with speech coding is the term voice coding. This term is more generic in the sense that
Stekelenburg, Jeroen J; Keetels, Mirjam; Vroomen, Jean
2018-05-01
Numerous studies have demonstrated that the vision of lip movements can alter the perception of auditory speech syllables (McGurk effect). While there is ample evidence for integration of text and auditory speech, there are only a few studies on the orthographic equivalent of the McGurk effect. Here, we examined whether written text, like visual speech, can induce an illusory change in the perception of speech sounds on both the behavioural and neural levels. In a sound categorization task, we found that both text and visual speech changed the identity of speech sounds from an /aba/-/ada/ continuum, but the size of this audiovisual effect was considerably smaller for text than visual speech. To examine at which level in the information processing hierarchy these multisensory interactions occur, we recorded electroencephalography in an audiovisual mismatch negativity (MMN, a component of the event-related potential reflecting preattentive auditory change detection) paradigm in which deviant text or visual speech was used to induce an illusory change in a sequence of ambiguous sounds halfway between /aba/ and /ada/. We found that only deviant visual speech induced an MMN, but not deviant text, which induced a late P3-like positive potential. These results demonstrate that text has much weaker effects on sound processing than visual speech does, possibly because text has different biological roots than visual speech. © 2018 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Closed circuit TV system automatically guides welding arc
NASA Technical Reports Server (NTRS)
Stephans, D. L.; Wall, W. A., Jr.
1968-01-01
Closed circuit television /CCTV/ system automatically guides a welding torch to position the welding arc accurately along weld seams. Digital counting and logic techniques incorporated in the control circuitry, ensure performance reliability.
The persuasiveness of synthetic speech versus human speech.
Stern, S E; Mullennix, J W; Dyson, C; Wilson, S J
1999-12-01
Is computer-synthesized speech as persuasive as the human voice when presenting an argument? After completing an attitude pretest, 193 participants were randomly assigned to listen to a persuasive appeal under three conditions: a high-quality synthesized speech system (DECtalk Express), a low-quality synthesized speech system (Monologue), and a tape recording of a human voice. Following the appeal, participants completed a posttest attitude survey and a series of questionnaires designed to assess perceptions of speech qualities, perceptions of the speaker, and perceptions of the message. The human voice was generally perceived more favorably than the computer-synthesized voice, and the speaker was perceived more favorably when the voice was a human voice than when it was computer synthesized. There was, however, no evidence that computerized speech, as compared with the human voice, affected persuasion or perceptions of the message. Actual or potential applications of this research include issues that should be considered when designing synthetic speech systems.
Davis, Chris; Kislyuk, Daniel; Kim, Jeesun; Sams, Mikko
2008-11-25
We used whole-head magnetoencephalograpy (MEG) to record changes in neuromagnetic N100m responses generated in the left and right auditory cortex as a function of the match between visual and auditory speech signals. Stimuli were auditory-only (AO) and auditory-visual (AV) presentations of /pi/, /ti/ and /vi/. Three types of intensity matched auditory stimuli were used: intact speech (Normal), frequency band filtered speech (Band) and speech-shaped white noise (Noise). The behavioural task was to detect the /vi/ syllables which comprised 12% of stimuli. N100m responses were measured to averaged /pi/ and /ti/ stimuli. Behavioural data showed that identification of the stimuli was faster and more accurate for Normal than for Band stimuli, and for Band than for Noise stimuli. Reaction times were faster for AV than AO stimuli. MEG data showed that in the left hemisphere, N100m to both AO and AV stimuli was largest for the Normal, smaller for Band and smallest for Noise stimuli. In the right hemisphere, Normal and Band AO stimuli elicited N100m responses of quite similar amplitudes, but N100m amplitude to Noise was about half of that. There was a reduction in N100m for the AV compared to the AO conditions. The size of this reduction for each stimulus type was same in the left hemisphere but graded in the right (being largest to the Normal, smaller to the Band and smallest to the Noise stimuli). The N100m decrease for the Normal stimuli was significantly larger in the right than in the left hemisphere. We suggest that the effect of processing visual speech seen in the right hemisphere likely reflects suppression of the auditory response based on AV cues for place of articulation.
Davidow, Jason H; Ingham, Roger J
2013-01-01
This study examined the effect of speech rate on phonated intervals (PIs), in order to test whether a reduction in the frequency of short PIs is an important part of the fluency-inducing mechanism of chorus reading. The influence of speech rate on stuttering frequency, speaker-judged speech effort, and listener-judged naturalness was also examined. An added purpose was to determine if chorus reading could be further refined so as to provide a perceptual guide for gauging the level of physical effort exerted during speech production. A repeated-measures design was used to compare data obtained during control reading conditions and during several chorus reading conditions produced at different speech rates. Participants included 8 persons who stutter (PWS) between the ages of 16 and 32 years. There were significant reductions in the frequency of short PIs from the habitual reading condition during slower chorus conditions, no change when speech rates were matched between habitual reading and chorus conditions, and an increase in the frequency of short PIs during chorus reading produced at a faster rate than the habitual condition. Speech rate did not have an effect on stuttering frequency during chorus reading. In general, speech effort ratings improved and naturalness ratings worsened as speech rate decreased. These results provide evidence that (a) a reduction in the frequency of short PIs is not necessary for fluency improvement during chorus reading, and (b) speech rate may be altered to provide PWS with a more appropriate reference for how physically effortful normally fluent speech production should be. Future investigations should examine the necessity of changes in the activation of neural regions during chorus reading, the possibility of defining individualized units on a 9-point effort scale, and if there are upper and lower speech rate boundaries for receiving ratings of "highly natural sounding" speech during chorus reading. The reader will be able to: (1
Degraded neural and behavioral processing of speech sounds in a rat model of Rett syndrome
Engineer, Crystal T.; Rahebi, Kimiya C.; Borland, Michael S.; Buell, Elizabeth P.; Centanni, Tracy M.; Fink, Melyssa K.; Im, Kwok W.; Wilson, Linda G.; Kilgard, Michael P.
2015-01-01
Individuals with Rett syndrome have greatly impaired speech and language abilities. Auditory brainstem responses to sounds are normal, but cortical responses are highly abnormal. In this study, we used the novel rat Mecp2 knockout model of Rett syndrome to document the neural and behavioral processing of speech sounds. We hypothesized that both speech discrimination ability and the neural response to speech sounds would be impaired in Mecp2 rats. We expected that extensive speech training would improve speech discrimination ability and the cortical response to speech sounds. Our results reveal that speech responses across all four auditory cortex fields of Mecp2 rats were hyperexcitable, responded slower, and were less able to follow rapidly presented sounds. While Mecp2 rats could accurately perform consonant and vowel discrimination tasks in quiet, they were significantly impaired at speech sound discrimination in background noise. Extensive speech training improved discrimination ability. Training shifted cortical responses in both Mecp2 and control rats to favor the onset of speech sounds. While training increased the response to low frequency sounds in control rats, the opposite occurred in Mecp2 rats. Although neural coding and plasticity are abnormal in the rat model of Rett syndrome, extensive therapy appears to be effective. These findings may help to explain some aspects of communication deficits in Rett syndrome and suggest that extensive rehabilitation therapy might prove beneficial. PMID:26321676
Speech perception in noise with a harmonic complex excited vocoder.
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.
ERIC Educational Resources Information Center
Nash, Hannah M.; Gooch, Debbie; Hulme, Charles; Mahajan, Yatin; McArthur, Genevieve; Steinmetzger, Kurt; Snowling, Margaret J.
2017-01-01
The "automatic letter-sound integration hypothesis" (Blomert, [Blomert, L., 2011]) proposes that dyslexia results from a failure to fully integrate letters and speech sounds into automated audio-visual objects. We tested this hypothesis in a sample of English-speaking children with dyslexic difficulties (N = 13) and samples of…
Fricative Contrast and Coarticulation in Children With and Without Speech Sound Disorders
Mailend, Marja-Liisa
2017-01-01
Purpose The purpose of this study was, first, to expand our understanding of typical speech development regarding segmental contrast and anticipatory coarticulation, and second, to explore the potential diagnostic utility of acoustic measures of fricative contrast and anticipatory coarticulation in children with speech sound disorders (SSD). Method In a cross-sectional design, 10 adults, 17 typically developing children, and 11 children with SSD repeated carrier phrases with novel words with fricatives (/s/, /ʃ/). Dependent measures were 2 ratios derived from spectral mean, obtained from perceptually accurate tokens. Group analyses compared adults and typically developing children; individual children with SSD were compared to their respective typically developing peers. Results Typically developing children demonstrated smaller fricative acoustic contrast than adults but similar coarticulatory patterns. Three children with SSD showed smaller fricative acoustic contrast than their typically developing peers, and 2 children showed abnormal coarticulation. The 2 children with abnormal coarticulation both had a clinical diagnosis of childhood apraxia of speech; no clear pattern was evident regarding SSD subtype for smaller fricative contrast. Conclusions Children have not reached adult-like speech motor control for fricative production by age 10 even when fricatives are perceptually accurate. Present findings also suggest that abnormal coarticulation but not reduced fricative contrast is SSD-subtype–specific. Supplemental Materials S1: https://doi.org/10.23641/asha.5103070. S2 and S3: https://doi.org/10.23641/asha.5106508 PMID:28654946
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.
Perceiving non-native speech: Word segmentation
NASA Astrophysics Data System (ADS)
Mondini, Michèle; Miller, Joanne L.
2004-05-01
One important source of information listeners use to segment speech into discrete words is allophonic variation at word junctures. Previous research has shown that non-native speakers impose their native-language phonetic norms on their second language; as a consequence, non-native speech may (in some cases) exhibit altered patterns of allophonic variation at word junctures. We investigated the perceptual consequences of this for word segmentation by presenting native-English listeners with English word pairs produced either by six native-English speakers or six highly fluent, native-French speakers of English. The target word pairs had contrastive word juncture involving voiceless stop consonants (e.g., why pink/wipe ink; gray ties/great eyes; we cash/weak ash). The task was to identify randomized instances of each individual target word pair (as well as control pairs) by selecting one of four possible choices (e.g., why pink, wipe ink, why ink, wipe pink). Overall, listeners were more accurate in identifying target word pairs produced by the native-English speakers than by the non-native English speakers. These findings suggest that one contribution to the processing cost associated with listening to non-native speech may be the presence of altered allophonic information important for word segmentation. [Work supported by NIH/NIDCD.
Bae, Yong-Chan; Choi, Soo-Jong; Lee, Jae-Woo; Seo, Hyoung-Joon
2015-03-01
Operative techniques in performing cleft palate repair have gradually evolved to achieve better speech ability with its main focus on palatal lengthening and accurate approximation of the velar musculature. The authors doubted whether the extent of palatal lengthening would be directly proportional to the speech outcome. Patients with incomplete cleft palates who went into surgery before 18 months of age were intended for this study. Cases with associated syndromes, mental retardation, hearing loss, or presence of postoperative complications were excluded from the analysis. Palatal length was measured by the authors' devised method before and immediately after the cleft palate repair. Postoperative speech outcome was evaluated around 4 years by a definite pronunciation scoring system. Statistical analysis was carried out between the extent of palatal lengthening and the postoperative pronunciation score by Spearman correlation coefficient method. However, the authors could not find any significant correlation. Although the need for additional research on other variables affecting speech outcome is unequivocal, we carefully conclude that other intraoperative constituents such as accurate reapproximation of the velar musculature should be emphasized more in cleft palate repair rather than palatal lengthening itself.
Mostafavi, Kamal; Tutunea-Fatan, O Remus; Bordatchev, Evgueni V; Johnson, James A
2014-12-01
The strong advent of computer-assisted technologies experienced by the modern orthopedic surgery prompts for the expansion of computationally efficient techniques to be built on the broad base of computer-aided engineering tools that are readily available. However, one of the common challenges faced during the current developmental phase continues to remain the lack of reliable frameworks to allow a fast and precise conversion of the anatomical information acquired through computer tomography to a format that is acceptable to computer-aided engineering software. To address this, this study proposes an integrated and automatic framework capable to extract and then postprocess the original imaging data to a common planar and closed B-Spline representation. The core of the developed platform relies on the approximation of the discrete computer tomography data by means of an original two-step B-Spline fitting technique based on successive deformations of the control polygon. In addition to its rapidity and robustness, the developed fitting technique was validated to produce accurate representations that do not deviate by more than 0.2 mm with respect to alternate representations of the bone geometry that were obtained through different-contact-based-data acquisition or data processing methods. © IMechE 2014.
Speech production in children with Down's syndrome: The effects of reading, naming and imitation.
Knight, Rachael-Anne; Kurtz, Scilla; Georgiadou, Ioanna
2015-01-01
People with DS are known to have difficulties with expressive language, and often have difficulties with intelligibility. They often have stronger visual than verbal short-term memory skills and, therefore, reading has often been suggested as an intervention for speech and language in this population. However, there is as yet no firm evidence that reading can improve speech outcomes. This study aimed to compare reading, picture naming and repetition for the same 10 words, to identify if the speech of eight children with DS (aged 11-14 years) was more accurate, consistent and intelligible when reading. Results show that children were slightly, yet significantly, more accurate and intelligible when they read words compared with when they produced those words in naming or imitation conditions although the reduction in inconsistency was non-significant. The results of this small-scale study provide tentative support for previous claims about the benefits of reading for children with DS. The mechanisms behind a facilitatory effect of reading are considered, and directions are identified for future research.
An overview of neural function and feedback control in human communication.
Hood, L J
1998-01-01
The speech and hearing mechanisms depend on accurate sensory information and intact feedback mechanisms to facilitate communication. This article provides a brief overview of some components of the nervous system important for human communication and some electrophysiological methods used to measure cortical function in humans. An overview of automatic control and feedback mechanisms in general and as they pertain to the speech motor system and control of the hearing periphery is also presented, along with a discussion of how the speech and auditory systems interact.
Speech Perception Deficits in Mandarin-Speaking School-Aged Children with Poor Reading Comprehension
Liu, Huei-Mei; Tsao, Feng-Ming
2017-01-01
Previous studies have shown that children learning alphabetic writing systems who have language impairment or dyslexia exhibit speech perception deficits. However, whether such deficits exist in children learning logographic writing systems who have poor reading comprehension remains uncertain. To further explore this issue, the present study examined speech perception deficits in Mandarin-speaking children with poor reading comprehension. Two self-designed tasks, consonant categorical perception task and lexical tone discrimination task were used to compare speech perception performance in children (n = 31, age range = 7;4–10;2) with poor reading comprehension and an age-matched typically developing group (n = 31, age range = 7;7–9;10). Results showed that the children with poor reading comprehension were less accurate in consonant and lexical tone discrimination tasks and perceived speech contrasts less categorically than the matched group. The correlations between speech perception skills (i.e., consonant and lexical tone discrimination sensitivities and slope of consonant identification curve) and individuals’ oral language and reading comprehension were stronger than the correlations between speech perception ability and word recognition ability. In conclusion, the results revealed that Mandarin-speaking children with poor reading comprehension exhibit less-categorized speech perception, suggesting that imprecise speech perception, especially lexical tone perception, is essential to account for reading learning difficulties in Mandarin-speaking children. PMID:29312031
Speech entrainment enables patients with Broca’s aphasia to produce fluent speech
Hubbard, H. Isabel; Hudspeth, Sarah Grace; Holland, Audrey L.; Bonilha, Leonardo; Fromm, Davida; Rorden, Chris
2012-01-01
A distinguishing feature of Broca’s aphasia is non-fluent halting speech typically involving one to three words per utterance. Yet, despite such profound impairments, some patients can mimic audio-visual speech stimuli enabling them to produce fluent speech in real time. We call this effect ‘speech entrainment’ and reveal its neural mechanism as well as explore its usefulness as a treatment for speech production in Broca’s aphasia. In Experiment 1, 13 patients with Broca’s aphasia were tested in three conditions: (i) speech entrainment with audio-visual feedback where they attempted to mimic a speaker whose mouth was seen on an iPod screen; (ii) speech entrainment with audio-only feedback where patients mimicked heard speech; and (iii) spontaneous speech where patients spoke freely about assigned topics. The patients produced a greater variety of words using audio-visual feedback compared with audio-only feedback and spontaneous speech. No difference was found between audio-only feedback and spontaneous speech. In Experiment 2, 10 of the 13 patients included in Experiment 1 and 20 control subjects underwent functional magnetic resonance imaging to determine the neural mechanism that supports speech entrainment. Group results with patients and controls revealed greater bilateral cortical activation for speech produced during speech entrainment compared with spontaneous speech at the junction of the anterior insula and Brodmann area 47, in Brodmann area 37, and unilaterally in the left middle temporal gyrus and the dorsal portion of Broca’s area. Probabilistic white matter tracts constructed for these regions in the normal subjects revealed a structural network connected via the corpus callosum and ventral fibres through the extreme capsule. Unilateral areas were connected via the arcuate fasciculus. In Experiment 3, all patients included in Experiment 1 participated in a 6-week treatment phase using speech entrainment to improve speech production
See, Rachel L; Driscoll, Virginia D; Gfeller, Kate; Kliethermes, Stephanie; Oleson, Jacob
2013-04-01
Cochlear implant (CI) users have difficulty perceiving some intonation cues in speech and melodic contours because of poor frequency selectivity in the cochlear implant signal. To assess perceptual accuracy of normal hearing (NH) children and pediatric CI users on speech intonation (prosody), melodic contour, and pitch ranking, and to determine potential predictors of outcomes. Does perceptual accuracy for speech intonation or melodic contour differ as a function of auditory status (NH, CI), perceptual category (falling versus rising intonation/contour), pitch perception, or individual differences (e.g., age, hearing history)? NH and CI groups were tested on recognition of falling intonation/contour versus rising intonation/contour presented in both spoken and melodic (sung) conditions. Pitch ranking was also tested. Outcomes were correlated with variables of age, hearing history, HINT, and CNC scores. The CI group was significantly less accurate than the NH group in spoken (CI, M = 63.1%; NH, M = 82.1%) and melodic (CI, M = 61.6%; NH, M = 84.2%) conditions. The CI group was more accurate in recognizing rising contour in the melodic condition compared with rising intonation in the spoken condition. Pitch ranking was a significant predictor of outcome for both groups in falling intonation and rising melodic contour; age at testing and hearing history variables were not predictive of outcomes. Children with CIs were less accurate than NH children in perception of speech intonation, melodic contour, and pitch ranking. However, the larger pitch excursions of the melodic condition may assist in recognition of the rising inflection associated with the interrogative form.
Semi Automatic Ontology Instantiation in the domain of Risk Management
NASA Astrophysics Data System (ADS)
Makki, Jawad; Alquier, Anne-Marie; Prince, Violaine
One of the challenging tasks in the context of Ontological Engineering is to automatically or semi-automatically support the process of Ontology Learning and Ontology Population from semi-structured documents (texts). In this paper we describe a Semi-Automatic Ontology Instantiation method from natural language text, in the domain of Risk Management. This method is composed from three steps 1 ) Annotation with part-of-speech tags, 2) Semantic Relation Instances Extraction, 3) Ontology instantiation process. It's based on combined NLP techniques using human intervention between steps 2 and 3 for control and validation. Since it heavily relies on linguistic knowledge it is not domain dependent which is a good feature for portability between the different fields of risk management application. The proposed methodology uses the ontology of the PRIMA1 project (supported by the European community) as a Generic Domain Ontology and populates it via an available corpus. A first validation of the approach is done through an experiment with Chemical Fact Sheets from Environmental Protection Agency2.
Do perceived context pictures automatically activate their phonological code?
Jescheniak, Jörg D; Oppermann, Frank; Hantsch, Ansgar; Wagner, Valentin; Mädebach, Andreas; Schriefers, Herbert
2009-01-01
Morsella and Miozzo (Morsella, E., & Miozzo, M. (2002). Evidence for a cascade model of lexical access in speech production. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28, 555-563) have reported that the to-be-ignored context pictures become phonologically activated when participants name a target picture, and took this finding as support for cascaded models of lexical retrieval in speech production. In a replication and extension of their experiment in German, we failed to obtain priming effects from context pictures phonologically related to a to-be-named target picture. By contrast, corresponding context words (i.e., the names of the respective pictures) and the same context pictures, when used in an identity condition, did reliably facilitate the naming process. This pattern calls into question the generality of the claim advanced by Morsella and Miozzo that perceptual processing of pictures in the context of a naming task automatically leads to the activation of corresponding lexical-phonological codes.
Digital signal processing algorithms for automatic voice recognition
NASA Technical Reports Server (NTRS)
Botros, Nazeih M.
1987-01-01
The current digital signal analysis algorithms are investigated that are implemented in automatic voice recognition algorithms. Automatic voice recognition means, the capability of a computer to recognize and interact with verbal commands. The digital signal is focused on, rather than the linguistic, analysis of speech signal. Several digital signal processing algorithms are available for voice recognition. Some of these algorithms are: Linear Predictive Coding (LPC), Short-time Fourier Analysis, and Cepstrum Analysis. Among these algorithms, the LPC is the most widely used. This algorithm has short execution time and do not require large memory storage. However, it has several limitations due to the assumptions used to develop it. The other 2 algorithms are frequency domain algorithms with not many assumptions, but they are not widely implemented or investigated. However, with the recent advances in the digital technology, namely signal processors, these 2 frequency domain algorithms may be investigated in order to implement them in voice recognition. This research is concerned with real time, microprocessor based recognition algorithms.
Speech Anxiety: The Importance of Identification in the Basic Speech Course.
ERIC Educational Resources Information Center
Mandeville, Mary Y.
A study investigated speech anxiety in the basic speech course by means of pre and post essays. Subjects, 73 students in 3 classes in the basic speech course at a southwestern multiuniversity, wrote a two-page essay on their perceptions of their speech anxiety before the first speaking project. Students discussed speech anxiety in class and were…
NASA Astrophysics Data System (ADS)
Endah, S. N.; Nugraheni, D. M. K.; Adhy, S.; Sutikno
2017-04-01
According to Law No. 32 of 2002 and the Indonesian Broadcasting Commission Regulation No. 02/P/KPI/12/2009 & No. 03/P/KPI/12/2009, stated that broadcast programs should not scold with harsh words, not harass, insult or demean minorities and marginalized groups. However, there are no suitable tools to censor those words automatically. Therefore, researches to develop a system of intelligent software to censor the words automatically are needed. To conduct censor, the system must be able to recognize the words in question. This research proposes the classification of speech divide into two classes using Support Vector Machine (SVM), first class is set of rude words and the second class is set of properly words. The speech pitch values as an input in SVM, it used for the development of the system for the Indonesian rude swear word. The results of the experiment show that SVM is good for this system.
Analysis of speech sounds is left-hemisphere predominant at 100-150ms after sound onset.
Rinne, T; Alho, K; Alku, P; Holi, M; Sinkkonen, J; Virtanen, J; Bertrand, O; Näätänen, R
1999-04-06
Hemispheric specialization of human speech processing has been found in brain imaging studies using fMRI and PET. Due to the restricted time resolution, these methods cannot, however, determine the stage of auditory processing at which this specialization first emerges. We used a dense electrode array covering the whole scalp to record the mismatch negativity (MMN), an event-related brain potential (ERP) automatically elicited by occasional changes in sounds, which ranged from non-phonetic (tones) to phonetic (vowels). MMN can be used to probe auditory central processing on a millisecond scale with no attention-dependent task requirements. Our results indicate that speech processing occurs predominantly in the left hemisphere at the early, pre-attentive level of auditory analysis.
Multimodal Speech Capture System for Speech Rehabilitation and Learning.
Sebkhi, Nordine; Desai, Dhyey; Islam, Mohammad; Lu, Jun; Wilson, Kimberly; Ghovanloo, Maysam
2017-11-01
Speech-language pathologists (SLPs) are trained to correct articulation of people diagnosed with motor speech disorders by analyzing articulators' motion and assessing speech outcome while patients speak. To assist SLPs in this task, we are presenting the multimodal speech capture system (MSCS) that records and displays kinematics of key speech articulators, the tongue and lips, along with voice, using unobtrusive methods. Collected speech modalities, tongue motion, lips gestures, and voice are visualized not only in real-time to provide patients with instant feedback but also offline to allow SLPs to perform post-analysis of articulators' motion, particularly the tongue, with its prominent but hardly visible role in articulation. We describe the MSCS hardware and software components, and demonstrate its basic visualization capabilities by a healthy individual repeating the words "Hello World." A proof-of-concept prototype has been successfully developed for this purpose, and will be used in future clinical studies to evaluate its potential impact on accelerating speech rehabilitation by enabling patients to speak naturally. Pattern matching algorithms to be applied to the collected data can provide patients with quantitative and objective feedback on their speech performance, unlike current methods that are mostly subjective, and may vary from one SLP to another.
ERIC Educational Resources Information Center
van Lieshout, Pascal H. H. M.; Bose, Arpita; Square, Paula A.; Steele, Catriona M.
2007-01-01
Apraxia of speech (AOS) is typically described as a motor-speech disorder with clinically well-defined symptoms, but without a clear understanding of the underlying problems in motor control. A number of studies have compared the speech of subjects with AOS to the fluent speech of controls, but only a few have included speech movement data and if…
Iuzzini-Seigel, Jenya; Hogan, Tiffany P; Green, Jordan R
2017-05-24
The current research sought to determine (a) if speech inconsistency is a core feature of childhood apraxia of speech (CAS) or if it is driven by comorbid language impairment that affects a large subset of children with CAS and (b) if speech inconsistency is a sensitive and specific diagnostic marker that can differentiate between CAS and speech delay. Participants included 48 children ranging between 4;7 to 17;8 (years;months) with CAS (n = 10), CAS + language impairment (n = 10), speech delay (n = 10), language impairment (n = 9), or typical development (n = 9). Speech inconsistency was assessed at phonemic and token-to-token levels using a variety of stimuli. Children with CAS and CAS + language impairment performed equivalently on all inconsistency assessments. Children with language impairment evidenced high levels of speech inconsistency on the phrase "buy Bobby a puppy." Token-to-token inconsistency of monosyllabic words and the phrase "buy Bobby a puppy" was sensitive and specific in differentiating children with CAS and speech delay, whereas inconsistency calculated on other stimuli (e.g., multisyllabic words) was less efficacious in differentiating between these disorders. Speech inconsistency is a core feature of CAS and is efficacious in differentiating between children with CAS and speech delay; however, sensitivity and specificity are stimuli dependent.
Automatic segmentation of time-lapse microscopy images depicting a live Dharma embryo.
Zacharia, Eleni; Bondesson, Maria; Riu, Anne; Ducharme, Nicole A; Gustafsson, Jan-Åke; Kakadiaris, Ioannis A
2011-01-01
Biological inferences about the toxicity of chemicals reached during experiments on the zebrafish Dharma embryo can be greatly affected by the analysis of the time-lapse microscopy images depicting the embryo. Among the stages of image analysis, automatic and accurate segmentation of the Dharma embryo is the most crucial and challenging. In this paper, an accurate and automatic segmentation approach for the segmentation of the Dharma embryo data obtained by fluorescent time-lapse microscopy is proposed. Experiments performed in four stacks of 3D images over time have shown promising results.
High accurate time system of the Low Latitude Meridian Circle.
NASA Astrophysics Data System (ADS)
Yang, Jing; Wang, Feng; Li, Zhiming
In order to obtain the high accurate time signal for the Low Latitude Meridian Circle (LLMC), a new GPS accurate time system is developed which include GPS, 1 MC frequency source and self-made clock system. The second signal of GPS is synchronously used in the clock system and information can be collected by a computer automatically. The difficulty of the cancellation of the time keeper can be overcomed by using this system.
Rapid tuning shifts in human auditory cortex enhance speech intelligibility
Holdgraf, Christopher R.; de Heer, Wendy; Pasley, Brian; Rieger, Jochem; Crone, Nathan; Lin, Jack J.; Knight, Robert T.; Theunissen, Frédéric E.
2016-01-01
Experience shapes our perception of the world on a moment-to-moment basis. This robust perceptual effect of experience parallels a change in the neural representation of stimulus features, though the nature of this representation and its plasticity are not well-understood. Spectrotemporal receptive field (STRF) mapping describes the neural response to acoustic features, and has been used to study contextual effects on auditory receptive fields in animal models. We performed a STRF plasticity analysis on electrophysiological data from recordings obtained directly from the human auditory cortex. Here, we report rapid, automatic plasticity of the spectrotemporal response of recorded neural ensembles, driven by previous experience with acoustic and linguistic information, and with a neurophysiological effect in the sub-second range. This plasticity reflects increased sensitivity to spectrotemporal features, enhancing the extraction of more speech-like features from a degraded stimulus and providing the physiological basis for the observed ‘perceptual enhancement' in understanding speech. PMID:27996965
Robust Recognition of Loud and Lombard speech in the Fighter Cockpit Environment
1988-08-01
the latter as inter-speaker variability. According to Zue [Z85j, inter-speaker variabilities can be attributed to sociolinguistic background, dialect...34 Journal of the Acoustical Society of America , Vol 50, 1971. [At74I B. S. Atal, "Linear prediction for speaker identification," Journal of the Acoustical...Society of America , Vol 55, 1974. [B771 B. Beek, E. P. Neuberg, and D. C. Hodge, "An Assessment of the Technology of Automatic Speech Recognition for
Achieving perceptually-accurate aural telepresence
NASA Astrophysics Data System (ADS)
Henderson, Paul D.
Immersive multimedia requires not only realistic visual imagery but also a perceptually-accurate aural experience. A sound field may be presented simultaneously to a listener via a loudspeaker rendering system using the direct sound from acoustic sources as well as a simulation or "auralization" of room acoustics. Beginning with classical Wave-Field Synthesis (WFS), improvements are made to correct for asymmetries in loudspeaker array geometry. Presented is a new Spatially-Equalized WFS (SE-WFS) technique to maintain the energy-time balance of a simulated room by equalizing the reproduced spectrum at the listener for a distribution of possible source angles. Each reproduced source or reflection is filtered according to its incidence angle to the listener. An SE-WFS loudspeaker array of arbitrary geometry reproduces the sound field of a room with correct spectral and temporal balance, compared with classically-processed WFS systems. Localization accuracy of human listeners in SE-WFS sound fields is quantified by psychoacoustical testing. At a loudspeaker spacing of 0.17 m (equivalent to an aliasing cutoff frequency of 1 kHz), SE-WFS exhibits a localization blur of 3 degrees, nearly equal to real point sources. Increasing the loudspeaker spacing to 0.68 m (for a cutoff frequency of 170 Hz) results in a blur of less than 5 degrees. In contrast, stereophonic reproduction is less accurate with a blur of 7 degrees. The ventriloquist effect is psychometrically investigated to determine the effect of an intentional directional incongruence between audio and video stimuli. Subjects were presented with prerecorded full-spectrum speech and motion video of a talker's head as well as broadband noise bursts with a static image. The video image was displaced from the audio stimulus in azimuth by varying amounts, and the perceived auditory location measured. A strong bias was detectable for small angular discrepancies between audio and video stimuli for separations of less than 8
Burnett, Greg C.; Holzrichter, John F.; Ng, Lawrence C.
2002-01-01
Low power EM waves are used to detect motions of vocal tract tissues of the human speech system before, during, and after voiced speech. A voiced excitation function is derived. The excitation function provides speech production information to enhance speech characterization and to enable noise removal from human speech.
Maas, Edwin; Mailend, Marja-Liisa
2012-10-01
The purpose of this article is to present an argument for the use of online reaction time (RT) methods to the study of apraxia of speech (AOS) and to review the existing small literature in this area and the contributions it has made to our fundamental understanding of speech planning (deficits) in AOS. Following a brief description of limitations of offline perceptual methods, we provide a narrative review of various types of RT paradigms from the (speech) motor programming and psycholinguistic literatures and their (thus far limited) application with AOS. On the basis of the review of the literature, we conclude that with careful consideration of potential challenges and caveats, RT approaches hold great promise to advance our understanding of AOS, in particular with respect to the speech planning processes that generate the speech signal before initiation. A deeper understanding of the nature and time course of speech planning and its disruptions in AOS may enhance diagnosis and treatment for AOS. Only a handful of published studies on apraxia of speech have used reaction time methods. However, these studies have provided deeper insight into speech planning impairments in AOS based on a variety of experimental paradigms.
Head movements encode emotions during speech and song.
Livingstone, Steven R; Palmer, Caroline
2016-04-01
When speaking or singing, vocalists often move their heads in an expressive fashion, yet the influence of emotion on vocalists' head motion is unknown. Using a comparative speech/song task, we examined whether vocalists' intended emotions influence head movements and whether those movements influence the perceived emotion. In Experiment 1, vocalists were recorded with motion capture while speaking and singing each statement with different emotional intentions (very happy, happy, neutral, sad, very sad). Functional data analyses showed that head movements differed in translational and rotational displacement across emotional intentions, yet were similar across speech and song, transcending differences in F0 (varied freely in speech, fixed in song) and lexical variability. Head motion specific to emotional state occurred before and after vocalizations, as well as during sound production, confirming that some aspects of movement were not simply a by-product of sound production. In Experiment 2, observers accurately identified vocalists' intended emotion on the basis of silent, face-occluded videos of head movements during speech and song. These results provide the first evidence that head movements encode a vocalist's emotional intent and that observers decode emotional information from these movements. We discuss implications for models of head motion during vocalizations and applied outcomes in social robotics and automated emotion recognition. (c) 2016 APA, all rights reserved).
Speech graphs provide a quantitative measure of thought disorder in psychosis.
Mota, Natalia B; Vasconcelos, Nivaldo A P; Lemos, Nathalia; Pieretti, Ana C; Kinouchi, Osame; Cecchi, Guillermo A; Copelli, Mauro; Ribeiro, Sidarta
2012-01-01
Psychosis has various causes, including mania and schizophrenia. Since the differential diagnosis of psychosis is exclusively based on subjective assessments of oral interviews with patients, an objective quantification of the speech disturbances that characterize mania and schizophrenia is in order. In principle, such quantification could be achieved by the analysis of speech graphs. A graph represents a network with nodes connected by edges; in speech graphs, nodes correspond to words and edges correspond to semantic and grammatical relationships. To quantify speech differences related to psychosis, interviews with schizophrenics, manics and normal subjects were recorded and represented as graphs. Manics scored significantly higher than schizophrenics in ten graph measures. Psychopathological symptoms such as logorrhea, poor speech, and flight of thoughts were grasped by the analysis even when verbosity differences were discounted. Binary classifiers based on speech graph measures sorted schizophrenics from manics with up to 93.8% of sensitivity and 93.7% of specificity. In contrast, sorting based on the scores of two standard psychiatric scales (BPRS and PANSS) reached only 62.5% of sensitivity and specificity. The results demonstrate that alterations of the thought process manifested in the speech of psychotic patients can be objectively measured using graph-theoretical tools, developed to capture specific features of the normal and dysfunctional flow of thought, such as divergence and recurrence. The quantitative analysis of speech graphs is not redundant with standard psychometric scales but rather complementary, as it yields a very accurate sorting of schizophrenics and manics. Overall, the results point to automated psychiatric diagnosis based not on what is said, but on how it is said.
Processing of prosodic changes in natural speech stimuli in school-age children.
Lindström, R; Lepistö, T; Makkonen, T; Kujala, T
2012-12-01
Speech prosody conveys information about important aspects of communication: the meaning of the sentence and the emotional state or intention of the speaker. The present study addressed processing of emotional prosodic changes in natural speech stimuli in school-age children (mean age 10 years) by recording the electroencephalogram, facial electromyography, and behavioral responses. The stimulus was a semantically neutral Finnish word uttered with four different emotional connotations: neutral, commanding, sad, and scornful. In the behavioral sound-discrimination task the reaction times were fastest for the commanding stimulus and longest for the scornful stimulus, and faster for the neutral than for the sad stimulus. EEG and EMG responses were measured during non-attentive oddball paradigm. Prosodic changes elicited a negative-going, fronto-centrally distributed neural response peaking at about 500 ms from the onset of the stimulus, followed by a fronto-central positive deflection, peaking at about 740 ms. For the commanding stimulus also a rapid negative deflection peaking at about 290 ms from stimulus onset was elicited. No reliable stimulus type specific rapid facial reactions were found. The results show that prosodic changes in natural speech stimuli activate pre-attentive neural change-detection mechanisms in school-age children. However, the results do not support the suggestion of automaticity of emotion specific facial muscle responses to non-attended emotional speech stimuli in children. Copyright © 2012 Elsevier B.V. All rights reserved.
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.
Speech perception of sine-wave signals by children with cochlear implants
Nittrouer, Susan; Kuess, Jamie; Lowenstein, Joanna H.
2015-01-01
Children need to discover linguistically meaningful structures in the acoustic speech signal. Being attentive to recurring, time-varying formant patterns helps in that process. However, that kind of acoustic structure may not be available to children with cochlear implants (CIs), thus hindering development. The major goal of this study was to examine whether children with CIs are as sensitive to time-varying formant structure as children with normal hearing (NH) by asking them to recognize sine-wave speech. The same materials were presented as speech in noise, as well, to evaluate whether any group differences might simply reflect general perceptual deficits on the part of children with CIs. Vocabulary knowledge, phonemic awareness, and “top-down” language effects were all also assessed. Finally, treatment factors were examined as possible predictors of outcomes. Results showed that children with CIs were as accurate as children with NH at recognizing sine-wave speech, but poorer at recognizing speech in noise. Phonemic awareness was related to that recognition. Top-down effects were similar across groups. Having had a period of bimodal stimulation near the time of receiving a first CI facilitated these effects. Results suggest that children with CIs have access to the important time-varying structure of vocal-tract formants. PMID:25994709
ERIC Educational Resources Information Center
Tedford, Thomas L., Ed.
This book is a collection of essays on free speech issues and attitudes, compiled by the Commission on Freedom of Speech of the Speech Communication Association. Four articles focus on freedom of speech in classroom situations as follows: a philosophic view of teaching free speech, effects of a course on free speech on student attitudes,…
Intelligibility for Binaural Speech with Discarded Low-SNR Speech Components.
Schoenmaker, Esther; van de Par, Steven
2016-01-01
Speech intelligibility in multitalker settings improves when the target speaker is spatially separated from the interfering speakers. A factor that may contribute to this improvement is the improved detectability of target-speech components due to binaural interaction in analogy to the Binaural Masking Level Difference (BMLD). This would allow listeners to hear target speech components within specific time-frequency intervals that have a negative SNR, similar to the improvement in the detectability of a tone in noise when these contain disparate interaural difference cues. To investigate whether these negative-SNR target-speech components indeed contribute to speech intelligibility, a stimulus manipulation was performed where all target components were removed when local SNRs were smaller than a certain criterion value. It can be expected that for sufficiently high criterion values target speech components will be removed that do contribute to speech intelligibility. For spatially separated speakers, assuming that a BMLD-like detection advantage contributes to intelligibility, degradation in intelligibility is expected already at criterion values below 0 dB SNR. However, for collocated speakers it is expected that higher criterion values can be applied without impairing speech intelligibility. Results show that degradation of intelligibility for separated speakers is only seen for criterion values of 0 dB and above, indicating a negligible contribution of a BMLD-like detection advantage in multitalker settings. These results show that the spatial benefit is related to a spatial separation of speech components at positive local SNRs rather than to a BMLD-like detection improvement for speech components at negative local SNRs.
Automatic lumbar spine measurement in CT images
NASA Astrophysics Data System (ADS)
Mao, Yunxiang; Zheng, Dong; Liao, Shu; Peng, Zhigang; Yan, Ruyi; Liu, Junhua; Dong, Zhongxing; Gong, Liyan; Zhou, Xiang Sean; Zhan, Yiqiang; Fei, Jun
2017-03-01
Accurate lumbar spine measurement in CT images provides an essential way for quantitative spinal diseases analysis such as spondylolisthesis and scoliosis. In today's clinical workflow, the measurements are manually performed by radiologists and surgeons, which is time consuming and irreproducible. Therefore, automatic and accurate lumbar spine measurement algorithm becomes highly desirable. In this study, we propose a method to automatically calculate five different lumbar spine measurements in CT images. There are three main stages of the proposed method: First, a learning based spine labeling method, which integrates both the image appearance and spine geometry information, is used to detect lumbar and sacrum vertebrae in CT images. Then, a multiatlases based image segmentation method is used to segment each lumbar vertebra and the sacrum based on the detection result. Finally, measurements are derived from the segmentation result of each vertebra. Our method has been evaluated on 138 spinal CT scans to automatically calculate five widely used clinical spine measurements. Experimental results show that our method can achieve more than 90% success rates across all the measurements. Our method also significantly improves the measurement efficiency compared to manual measurements. Besides benefiting the routine clinical diagnosis of spinal diseases, our method also enables the large scale data analytics for scientific and clinical researches.
Distributed neural signatures of natural audiovisual speech and music in the human auditory cortex.
Salmi, Juha; Koistinen, Olli-Pekka; Glerean, Enrico; Jylänki, Pasi; Vehtari, Aki; Jääskeläinen, Iiro P; Mäkelä, Sasu; Nummenmaa, Lauri; Nummi-Kuisma, Katarina; Nummi, Ilari; Sams, Mikko
2017-08-15
During a conversation or when listening to music, auditory and visual information are combined automatically into audiovisual objects. However, it is still poorly understood how specific type of visual information shapes neural processing of sounds in lifelike stimulus environments. Here we applied multi-voxel pattern analysis to investigate how naturally matching visual input modulates supratemporal cortex activity during processing of naturalistic acoustic speech, singing and instrumental music. Bayesian logistic regression classifiers with sparsity-promoting priors were trained to predict whether the stimulus was audiovisual or auditory, and whether it contained piano playing, speech, or singing. The predictive performances of the classifiers were tested by leaving one participant at a time for testing and training the model using the remaining 15 participants. The signature patterns associated with unimodal auditory stimuli encompassed distributed locations mostly in the middle and superior temporal gyrus (STG/MTG). A pattern regression analysis, based on a continuous acoustic model, revealed that activity in some of these MTG and STG areas were associated with acoustic features present in speech and music stimuli. Concurrent visual stimulus modulated activity in bilateral MTG (speech), lateral aspect of right anterior STG (singing), and bilateral parietal opercular cortex (piano). Our results suggest that specific supratemporal brain areas are involved in processing complex natural speech, singing, and piano playing, and other brain areas located in anterior (facial speech) and posterior (music-related hand actions) supratemporal cortex are influenced by related visual information. Those anterior and posterior supratemporal areas have been linked to stimulus identification and sensory-motor integration, respectively. Copyright © 2017 Elsevier Inc. All rights reserved.
Discrimination of brief speech sounds is impaired in rats with auditory cortex lesions
Porter, Benjamin A.; Rosenthal, Tara R.; Ranasinghe, Kamalini G.; Kilgard, Michael P.
2011-01-01
Auditory cortex (AC) lesions impair complex sound discrimination. However, a recent study demonstrated spared performance on an acoustic startle response test of speech discrimination following AC lesions (Floody et al., 2010). The current study reports the effects of AC lesions on two operant speech discrimination tasks. AC lesions caused a modest and quickly recovered impairment in the ability of rats to discriminate consonant-vowel-consonant speech sounds. This result seems to suggest that AC does not play a role in speech discrimination. However, the speech sounds used in both studies differed in many acoustic dimensions and an adaptive change in discrimination strategy could allow the rats to use an acoustic difference that does not require an intact AC to discriminate. Based on our earlier observation that the first 40 ms of the spatiotemporal activity patterns elicited by speech sounds best correlate with behavioral discriminations of these sounds (Engineer et al., 2008), we predicted that eliminating additional cues by truncating speech sounds to the first 40 ms would render the stimuli indistinguishable to a rat with AC lesions. Although the initial discrimination of truncated sounds took longer to learn, the final performance paralleled rats using full-length consonant-vowel-consonant sounds. After 20 days of testing, half of the rats using speech onsets received bilateral AC lesions. Lesions severely impaired speech onset discrimination for at least one-month post lesion. These results support the hypothesis that auditory cortex is required to accurately discriminate the subtle differences between similar consonant and vowel sounds. PMID:21167211
Automated classification of primary progressive aphasia subtypes from narrative speech transcripts.
Fraser, Kathleen C; Meltzer, Jed A; Graham, Naida L; Leonard, Carol; Hirst, Graeme; Black, Sandra E; Rochon, Elizabeth
2014-06-01
In the early stages of neurodegenerative disorders, individuals may exhibit a decline in language abilities that is difficult to quantify with standardized tests. Careful analysis of connected speech can provide valuable information about a patient's language capacities. To date, this type of analysis has been limited by its time-consuming nature. In this study, we present a method for evaluating and classifying connected speech in primary progressive aphasia using computational techniques. Syntactic and semantic features were automatically extracted from transcriptions of narrative speech for three groups: semantic dementia (SD), progressive nonfluent aphasia (PNFA), and healthy controls. Features that varied significantly between the groups were used to train machine learning classifiers, which were then tested on held-out data. We achieved accuracies well above baseline on the three binary classification tasks. An analysis of the influential features showed that in contrast with controls, both patient groups tended to use words which were higher in frequency (especially nouns for SD, and verbs for PNFA). The SD patients also tended to use words (especially nouns) that were higher in familiarity, and they produced fewer nouns, but more demonstratives and adverbs, than controls. The speech of the PNFA group tended to be slower and incorporate shorter words than controls. The patient groups were distinguished from each other by the SD patients' relatively increased use of words which are high in frequency and/or familiarity. Copyright © 2012 Elsevier Ltd. All rights reserved.
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
Synthesized speech rate and pitch effects on intelligibility of warning messages for pilots
NASA Technical Reports Server (NTRS)
Simpson, C. A.; Marchionda-Frost, K.
1984-01-01
In civilian and military operations, a future threat-warning system with a voice display could warn pilots of other traffic, obstacles in the flight path, and/or terrain during low-altitude helicopter flights. The present study was conducted to learn whether speech rate and voice pitch of phoneme-synthesized speech affects pilot accuracy and response time to typical threat-warning messages. Helicopter pilots engaged in an attention-demanding flying task and listened for voice threat warnings presented in a background of simulated helicopter cockpit noise. Performance was measured by flying-task performance, threat-warning intelligibility, and response time. Pilot ratings were elicited for the different voice pitches and speech rates. Significant effects were obtained only for response time and for pilot ratings, both as a function of speech rate. For the few cases when pilots forgot to respond to a voice message, they remembered 90 percent of the messages accurately when queried for their response 8 to 10 sec later.
See, Rachel L.; Driscoll, Virginia D.; Gfeller, Kate; Kliethermes, Stephanie; Oleson, Jacob
2013-01-01
Background Cochlear implant (CI) users have difficulty perceiving some intonation cues in speech and melodic contours because of poor frequency selectivity in the cochlear implant signal. Objectives To assess perceptual accuracy of normal hearing (NH) children and pediatric CI users on speech intonation (prosody), melodic contour, and pitch ranking, and to determine potential predictors of outcomes. Hypothesis Does perceptual accuracy for speech intonation or melodic contour differ as a function of auditory status (NH, CI), perceptual category (falling vs. rising intonation/contour), pitch perception, or individual differences (e.g., age, hearing history)? Method NH and CI groups were tested on recognition of falling intonation/contour vs. rising intonation/contour presented in both spoken and melodic (sung) conditions. Pitch ranking was also tested. Outcomes were correlated with variables of age, hearing history, HINT, and CNC scores. Results The CI group was significantly less accurate than the NH group in spoken (CI, M=63.1 %; NH, M=82.1%) and melodic (CI, M=61.6%; NH, M=84.2%) conditions. The CI group was more accurate in recognizing rising contour in the melodic condition compared with rising intonation in the spoken condition. Pitch ranking was a significant predictor of outcome for both groups in falling intonation and rising melodic contour; age at testing and hearing history variables were not predictive of outcomes. Conclusions Children with CIs were less accurate than NH children in perception of speech intonation, melodic contour, and pitch ranking. However, the larger pitch excursions of the melodic condition may assist in recognition of the rising inflection associated with the interrogative form. PMID:23442568
Giving speech a hand: gesture modulates activity in auditory cortex during speech perception.
Hubbard, Amy L; Wilson, Stephen M; Callan, Daniel E; Dapretto, Mirella
2009-03-01
Viewing hand gestures during face-to-face communication affects speech perception and comprehension. Despite the visible role played by gesture in social interactions, relatively little is known about how the brain integrates hand gestures with co-occurring speech. Here we used functional magnetic resonance imaging (fMRI) and an ecologically valid paradigm to investigate how beat gesture-a fundamental type of hand gesture that marks speech prosody-might impact speech perception at the neural level. Subjects underwent fMRI while listening to spontaneously-produced speech accompanied by beat gesture, nonsense hand movement, or a still body; as additional control conditions, subjects also viewed beat gesture, nonsense hand movement, or a still body all presented without speech. Validating behavioral evidence that gesture affects speech perception, bilateral nonprimary auditory cortex showed greater activity when speech was accompanied by beat gesture than when speech was presented alone. Further, the left superior temporal gyrus/sulcus showed stronger activity when speech was accompanied by beat gesture than when speech was accompanied by nonsense hand movement. Finally, the right planum temporale was identified as a putative multisensory integration site for beat gesture and speech (i.e., here activity in response to speech accompanied by beat gesture was greater than the summed responses to speech alone and beat gesture alone), indicating that this area may be pivotally involved in synthesizing the rhythmic aspects of both speech and gesture. Taken together, these findings suggest a common neural substrate for processing speech and gesture, likely reflecting their joint communicative role in social interactions.
Giving Speech a Hand: Gesture Modulates Activity in Auditory Cortex During Speech Perception
Hubbard, Amy L.; Wilson, Stephen M.; Callan, Daniel E.; Dapretto, Mirella
2008-01-01
Viewing hand gestures during face-to-face communication affects speech perception and comprehension. Despite the visible role played by gesture in social interactions, relatively little is known about how the brain integrates hand gestures with co-occurring speech. Here we used functional magnetic resonance imaging (fMRI) and an ecologically valid paradigm to investigate how beat gesture – a fundamental type of hand gesture that marks speech prosody – might impact speech perception at the neural level. Subjects underwent fMRI while listening to spontaneously-produced speech accompanied by beat gesture, nonsense hand movement, or a still body; as additional control conditions, subjects also viewed beat gesture, nonsense hand movement, or a still body all presented without speech. Validating behavioral evidence that gesture affects speech perception, bilateral nonprimary auditory cortex showed greater activity when speech was accompanied by beat gesture than when speech was presented alone. Further, the left superior temporal gyrus/sulcus showed stronger activity when speech was accompanied by beat gesture than when speech was accompanied by nonsense hand movement. Finally, the right planum temporale was identified as a putative multisensory integration site for beat gesture and speech (i.e., here activity in response to speech accompanied by beat gesture was greater than the summed responses to speech alone and beat gesture alone), indicating that this area may be pivotally involved in synthesizing the rhythmic aspects of both speech and gesture. Taken together, these findings suggest a common neural substrate for processing speech and gesture, likely reflecting their joint communicative role in social interactions. PMID:18412134
Inner Speech's Relationship with Overt Speech in Poststroke Aphasia
ERIC Educational Resources Information Center
Stark, Brielle C.; Geva, Sharon; Warburton, Elizabeth A.
2017-01-01
Purpose: Relatively preserved inner speech alongside poor overt speech has been documented in some persons with aphasia (PWA), but the relationship of overt speech with inner speech is still largely unclear, as few studies have directly investigated these factors. The present study investigates the relationship of relatively preserved inner speech…
Stasenko, Alena; Bonn, Cory; Teghipco, Alex; Garcea, Frank E.; Sweet, Catherine; Dombovy, Mary; McDonough, Joyce; Mahon, Bradford Z.
2015-01-01
In the last decade, the debate about the causal role of the motor system in speech perception has been reignited by demonstrations that motor processes are engaged during the processing of speech sounds. However, the exact role of the motor system in auditory speech processing remains elusive. Here we evaluate which aspects of auditory speech processing are affected, and which are not, in a stroke patient with dysfunction of the speech motor system. The patient’s spontaneous speech was marked by frequent phonological/articulatory errors, and those errors were caused, at least in part, by motor-level impairments with speech production. We found that the patient showed a normal phonemic categorical boundary when discriminating two nonwords that differ by a minimal pair (e.g., ADA-AGA). However, using the same stimuli, the patient was unable to identify or label the nonword stimuli (using a button-press response). A control task showed that he could identify speech sounds by speaker gender, ruling out a general labeling impairment. These data suggest that the identification (i.e. labeling) of nonword speech sounds may involve the speech motor system, but that the perception of speech sounds (i.e., discrimination) does not require the motor system. This means that motor processes are not causally involved in perception of the speech signal, and suggest that the motor system may be used when other cues (e.g., meaning, context) are not available. PMID:25951749
Predicting speech intelligibility in noise for hearing-critical jobs
NASA Astrophysics Data System (ADS)
Soli, Sigfrid D.; Laroche, Chantal; Giguere, Christian
2003-10-01
Many jobs require auditory abilities such as speech communication, sound localization, and sound detection. An employee for whom these abilities are impaired may constitute a safety risk for himself or herself, for fellow workers, and possibly for the general public. A number of methods have been used to predict these abilities from diagnostic measures of hearing (e.g., the pure-tone audiogram); however, these methods have not proved to be sufficiently accurate for predicting performance in the noise environments where hearing-critical jobs are performed. We have taken an alternative and potentially more accurate approach. A direct measure of speech intelligibility in noise, the Hearing in Noise Test (HINT), is instead used to screen individuals. The screening criteria are validated by establishing the empirical relationship between the HINT score and the auditory abilities of the individual, as measured in laboratory recreations of real-world workplace noise environments. The psychometric properties of the HINT enable screening of individuals with an acceptable amount of error. In this presentation, we will describe the predictive model and report the results of field measurements and laboratory studies used to provide empirical validation of the model. [Work supported by Fisheries and Oceans Canada.
Shen, Tianjie; Sie, Kathleen C Y
2014-11-01
Most speech disorders of childhood are treated with speech therapy. However, two conditions, ankyloglossia and velopharyngeal dysfunction, may be amenable to surgical intervention. It is important for surgeons to work with experienced speech language pathologists to diagnose the speech disorder. Children with articulation disorders related to ankyloglossia may benefit from frenuloplasty. Children with velopharyngeal dysfunction should have standardized clinical evaluation and instrumental asseessment of velopharyngeal function. Surgeons should develop a treatment protocol to optimize speech outcomes while minimizing morbidity. Copyright © 2014 Elsevier Inc. All rights reserved.
SCAMP: Automatic Astrometric and Photometric Calibration
NASA Astrophysics Data System (ADS)
Bertin, Emmanuel
2010-10-01
Astrometric and photometric calibrations have remained the most tiresome step in the reduction of large imaging surveys. SCAMP has been written to address this problem. The program efficiently computes accurate astrometric and photometric solutions for any arbitrary sequence of FITS images in a completely automatic way. SCAMP is released under the GNU General Public License.
How visual timing and form information affect speech and non-speech processing.
Kim, Jeesun; Davis, Chris
2014-10-01
Auditory speech processing is facilitated when the talker's face/head movements are seen. This effect is typically explained in terms of visual speech providing form and/or timing information. We determined the effect of both types of information on a speech/non-speech task (non-speech stimuli were spectrally rotated speech). All stimuli were presented paired with the talker's static or moving face. Two types of moving face stimuli were used: full-face versions (both spoken form and timing information available) and modified face versions (only timing information provided by peri-oral motion available). The results showed that the peri-oral timing information facilitated response time for speech and non-speech stimuli compared to a static face. An additional facilitatory effect was found for full-face versions compared to the timing condition; this effect only occurred for speech stimuli. We propose the timing effect was due to cross-modal phase resetting; the form effect to cross-modal priming. Copyright © 2014 Elsevier Inc. All rights reserved.
Speech communications in noise
NASA Technical Reports Server (NTRS)
1984-01-01
The physical characteristics of speech, the methods of speech masking measurement, and the effects of noise on speech communication are investigated. Topics include the speech signal and intelligibility, the effects of noise on intelligibility, the articulation index, and various devices for evaluating speech systems.
Overby, Megan; Carrell, Thomas; Bernthal, John
2007-10-01
This study examined 2nd-grade teachers' perceptions of the academic, social, and behavioral competence of students with speech sound disorders (SSDs). Forty-eight 2nd-grade teachers listened to 2 groups of sentences differing by intelligibility and pitch but spoken by a single 2nd grader. For each sentence group, teachers rated the speaker's academic, social, and behavioral competence using an adapted version of the Teacher Rating Scale of the Self-Perception Profile for Children (S. Harter, 1985) and completed 3 open-ended questions. The matched-guise design controlled for confounding speaker and stimuli variables that were inherent in prior studies. Statistically significant differences in teachers' expectations of children's academic, social, and behavioral performances were found between moderately intelligible and normal intelligibility speech. Teachers associated moderately intelligible low-pitched speech with more behavior problems than moderately intelligible high-pitched speech or either pitch with normal intelligibility. One third of the teachers reported that they could not accurately predict a child's school performance based on the child's speech skills, one third of the teachers causally related school difficulty to SSD, and one third of the teachers made no comment. Intelligibility and speaker pitch appear to be speech variables that influence teachers' perceptions of children's school performance.
Wołk, Agnieszka; Glinkowski, Wojciech
2017-01-01
People with speech, hearing, or mental impairment require special communication assistance, especially for medical purposes. Automatic solutions for speech recognition and voice synthesis from text are poor fits for communication in the medical domain because they are dependent on error-prone statistical models. Systems dependent on manual text input are insufficient. Recently introduced systems for automatic sign language recognition are dependent on statistical models as well as on image and gesture quality. Such systems remain in early development and are based mostly on minimal hand gestures unsuitable for medical purposes. Furthermore, solutions that rely on the Internet cannot be used after disasters that require humanitarian aid. We propose a high-speed, intuitive, Internet-free, voice-free, and text-free tool suited for emergency medical communication. Our solution is a pictogram-based application that provides easy communication for individuals who have speech or hearing impairment or mental health issues that impair communication, as well as foreigners who do not speak the local language. It provides support and clarification in communication by using intuitive icons and interactive symbols that are easy to use on a mobile device. Such pictogram-based communication can be quite effective and ultimately make people's lives happier, easier, and safer. PMID:29230254
Wołk, Krzysztof; Wołk, Agnieszka; Glinkowski, Wojciech
2017-01-01
People with speech, hearing, or mental impairment require special communication assistance, especially for medical purposes. Automatic solutions for speech recognition and voice synthesis from text are poor fits for communication in the medical domain because they are dependent on error-prone statistical models. Systems dependent on manual text input are insufficient. Recently introduced systems for automatic sign language recognition are dependent on statistical models as well as on image and gesture quality. Such systems remain in early development and are based mostly on minimal hand gestures unsuitable for medical purposes. Furthermore, solutions that rely on the Internet cannot be used after disasters that require humanitarian aid. We propose a high-speed, intuitive, Internet-free, voice-free, and text-free tool suited for emergency medical communication. Our solution is a pictogram-based application that provides easy communication for individuals who have speech or hearing impairment or mental health issues that impair communication, as well as foreigners who do not speak the local language. It provides support and clarification in communication by using intuitive icons and interactive symbols that are easy to use on a mobile device. Such pictogram-based communication can be quite effective and ultimately make people's lives happier, easier, and safer.
A window into the intoxicated mind? Speech as an index of psychoactive drug effects.
Bedi, Gillinder; Cecchi, Guillermo A; Slezak, Diego F; Carrillo, Facundo; Sigman, Mariano; de Wit, Harriet
2014-09-01
Abused drugs can profoundly alter mental states in ways that may motivate drug use. These effects are usually assessed with self-report, an approach that is vulnerable to biases. Analyzing speech during intoxication may present a more direct, objective measure, offering a unique 'window' into the mind. Here, we employed computational analyses of speech semantic and topological structure after ±3,4-methylenedioxymethamphetamine (MDMA; 'ecstasy') and methamphetamine in 13 ecstasy users. In 4 sessions, participants completed a 10-min speech task after MDMA (0.75 and 1.5 mg/kg), methamphetamine (20 mg), or placebo. Latent Semantic Analyses identified the semantic proximity between speech content and concepts relevant to drug effects. Graph-based analyses identified topological speech characteristics. Group-level drug effects on semantic distances and topology were assessed. Machine-learning analyses (with leave-one-out cross-validation) assessed whether speech characteristics could predict drug condition in the individual subject. Speech after MDMA (1.5 mg/kg) had greater semantic proximity than placebo to the concepts friend, support, intimacy, and rapport. Speech on MDMA (0.75 mg/kg) had greater proximity to empathy than placebo. Conversely, speech on methamphetamine was further from compassion than placebo. Classifiers discriminated between MDMA (1.5 mg/kg) and placebo with 88% accuracy, and MDMA (1.5 mg/kg) and methamphetamine with 84% accuracy. For the two MDMA doses, the classifier performed at chance. These data suggest that automated semantic speech analyses can capture subtle alterations in mental state, accurately discriminating between drugs. The findings also illustrate the potential for automated speech-based approaches to characterize clinically relevant alterations to mental state, including those occurring in psychiatric illness.
NASA Astrophysics Data System (ADS)
Viswanathan, V. R.; Makhoul, J.; Schwartz, R. M.; Huggins, A. W. F.
1982-04-01
The variable frame rate (VFR) transmission methodology developed, implemented, and tested in the years 1973-1978 for efficiently transmitting linear predictive coding (LPC) vocoder parameters extracted from the input speech at a fixed frame rate is reviewed. With the VFR method, parameters are transmitted only when their values have changed sufficiently over the interval since their preceding transmission. Two distinct approaches to automatic implementation of the VFR method are discussed. The first bases the transmission decisions on comparisons between the parameter values of the present frame and the last transmitted frame. The second, which is based on a functional perceptual model of speech, compares the parameter values of all the frames that lie in the interval between the present frame and the last transmitted frame against a linear model of parameter variation over that interval. Also considered is the application of VFR transmission to the design of narrow-band LPC speech coders with average bit rates of 2000-2400 bts/s.
Speech identification in noise: Contribution of temporal, spectral, and visual speech cues.
Kim, Jeesun; Davis, Chris; Groot, Christopher
2009-12-01
This study investigated the degree to which two types of reduced auditory signals (cochlear implant simulations) and visual speech cues combined for speech identification. The auditory speech stimuli were filtered to have only amplitude envelope cues or both amplitude envelope and spectral cues and were presented with/without visual speech. In Experiment 1, IEEE sentences were presented in quiet and noise. For in-quiet presentation, speech identification was enhanced by the addition of both spectral and visual speech cues. Due to a ceiling effect, the degree to which these effects combined could not be determined. In noise, these facilitation effects were more marked and were additive. Experiment 2 examined consonant and vowel identification in the context of CVC or VCV syllables presented in noise. For consonants, both spectral and visual speech cues facilitated identification and these effects were additive. For vowels, the effect of combined cues was underadditive, with the effect of spectral cues reduced when presented with visual speech cues. Analysis indicated that without visual speech, spectral cues facilitated the transmission of place information and vowel height, whereas with visual speech, they facilitated lip rounding, with little impact on the transmission of place information.
Reichenbach, Chagit S.; Braiman, Chananel; Schiff, Nicholas D.; Hudspeth, A. J.; Reichenbach, Tobias
2016-01-01
The auditory-brainstem response (ABR) to short and simple acoustical signals is an important clinical tool used to diagnose the integrity of the brainstem. The ABR is also employed to investigate the auditory brainstem in a multitude of tasks related to hearing, such as processing speech or selectively focusing on one speaker in a noisy environment. Such research measures the response of the brainstem to short speech signals such as vowels or words. Because the voltage signal of the ABR has a tiny amplitude, several hundred to a thousand repetitions of the acoustic signal are needed to obtain a reliable response. The large number of repetitions poses a challenge to assessing cognitive functions due to neural adaptation. Here we show that continuous, non-repetitive speech, lasting several minutes, may be employed to measure the ABR. Because the speech is not repeated during the experiment, the precise temporal form of the ABR cannot be determined. We show, however, that important structural features of the ABR can nevertheless be inferred. In particular, the brainstem responds at the fundamental frequency of the speech signal, and this response is modulated by the envelope of the voiced parts of speech. We accordingly introduce a novel measure that assesses the ABR as modulated by the speech envelope, at the fundamental frequency of speech and at the characteristic latency of the response. This measure has a high signal-to-noise ratio and can hence be employed effectively to measure the ABR to continuous speech. We use this novel measure to show that the ABR is weaker to intelligible speech than to unintelligible, time-reversed speech. The methods presented here can be employed for further research on speech processing in the auditory brainstem and can lead to the development of future clinical diagnosis of brainstem function. PMID:27303286
Poole, Matthew L; Brodtmann, Amy; Darby, David; Vogel, Adam P
2017-04-14
Our purpose was to create a comprehensive review of speech impairment in frontotemporal dementia (FTD), primary progressive aphasia (PPA), and progressive apraxia of speech in order to identify the most effective measures for diagnosis and monitoring, and to elucidate associations between speech and neuroimaging. Speech and neuroimaging data described in studies of FTD and PPA were systematically reviewed. A meta-analysis was conducted for speech measures that were used consistently in multiple studies. The methods and nomenclature used to describe speech in these disorders varied between studies. Our meta-analysis identified 3 speech measures which differentiate variants or healthy control-group participants (e.g., nonfluent and logopenic variants of PPA from all other groups, behavioral-variant FTD from a control group). Deficits within the frontal-lobe speech networks are linked to motor speech profiles of the nonfluent variant of PPA and progressive apraxia of speech. Motor speech impairment is rarely reported in semantic and logopenic variants of PPA. Limited data are available on motor speech impairment in the behavioral variant of FTD. Our review identified several measures of speech which may assist with diagnosis and classification, and consolidated the brain-behavior associations relating to speech in FTD, PPA, and progressive apraxia of speech.
Hayes-Harb, Rachel; Smith, Bruce L.; Bent, Tessa; Bradlow, Ann R.
2009-01-01
This study investigated the intelligibility of native and Mandarin-accented English speech for native English and native Mandarin listeners. The word-final voicing contrast was considered (as in minimal pairs such as `cub' and `cup') in a forced-choice word identification task. For these particular talkers and listeners, there was evidence of an interlanguage speech intelligibility benefit for listeners (i.e., native Mandarin listeners were more accurate than native English listeners at identifying Mandarin-accented English words). However, there was no evidence of an interlanguage speech intelligibility benefit for talkers (i.e., native Mandarin listeners did not find Mandarin-accented English speech more intelligible than native English speech). When listener and talker phonological proficiency (operationalized as accentedness) was taken into account, it was found that the interlanguage speech intelligibility benefit for listeners held only for the low phonological proficiency listeners and low phonological proficiency speech. The intelligibility data were also considered in relation to various temporal-acoustic properties of native English and Mandarin-accented English speech in effort to better understand the properties of speech that may contribute to the interlanguage speech intelligibility benefit. PMID:19606271
NASA Astrophysics Data System (ADS)
Thoonsaengngam, Rattapol; Tangsangiumvisai, Nisachon
This paper proposes an enhanced method for estimating the a priori Signal-to-Disturbance Ratio (SDR) to be employed in the Acoustic Echo and Noise Suppression (AENS) system for full-duplex hands-free communications. The proposed a priori SDR estimation technique is modified based upon the Two-Step Noise Reduction (TSNR) algorithm to suppress the background noise while preserving speech spectral components. In addition, a practical approach to determine accurately the Echo Spectrum Variance (ESV) is presented based upon the linear relationship assumption between the power spectrum of far-end speech and acoustic echo signals. The ESV estimation technique is then employed to alleviate the acoustic echo problem. The performance of the AENS system that employs these two proposed estimation techniques is evaluated through the Echo Attenuation (EA), Noise Attenuation (NA), and two speech distortion measures. Simulation results based upon real speech signals guarantee that our improved AENS system is able to mitigate efficiently the problem of acoustic echo and background noise, while preserving the speech quality and speech intelligibility.
Support for Debugging Automatically Parallelized Programs
NASA Technical Reports Server (NTRS)
Hood, Robert; Jost, Gabriele
2001-01-01
This viewgraph presentation provides information on support sources available for the automatic parallelization of computer program. CAPTools, a support tool developed at the University of Greenwich, transforms, with user guidance, existing sequential Fortran code into parallel message passing code. Comparison routines are then run for debugging purposes, in essence, ensuring that the code transformation was accurate.
Neurophysiology of speech differences in childhood apraxia of speech.
Preston, Jonathan L; Molfese, Peter J; Gumkowski, Nina; Sorcinelli, Andrea; Harwood, Vanessa; Irwin, Julia R; Landi, Nicole
2014-01-01
Event-related potentials (ERPs) were recorded during a picture naming task of simple and complex words in children with typical speech and with childhood apraxia of speech (CAS). Results reveal reduced amplitude prior to speaking complex (multisyllabic) words relative to simple (monosyllabic) words for the CAS group over the right hemisphere during a time window thought to reflect phonological encoding of word forms. Group differences were also observed prior to production of spoken tokens regardless of word complexity during a time window just prior to speech onset (thought to reflect motor planning/programming). Results suggest differences in pre-speech neurolinguistic processes.
Neurophysiology of Speech Differences in Childhood Apraxia of Speech
Preston, Jonathan L.; Molfese, Peter J.; Gumkowski, Nina; Sorcinelli, Andrea; Harwood, Vanessa; Irwin, Julia; Landi, Nicole
2014-01-01
Event-related potentials (ERPs) were recorded during a picture naming task of simple and complex words in children with typical speech and with childhood apraxia of speech (CAS). Results reveal reduced amplitude prior to speaking complex (multisyllabic) words relative to simple (monosyllabic) words for the CAS group over the right hemisphere during a time window thought to reflect phonological encoding of word forms. Group differences were also observed prior to production of spoken tokens regardless of word complexity during a time window just prior to speech onset (thought to reflect motor planning/programming). Results suggest differences in pre-speech neurolinguistic processes. PMID:25090016
Bowers, Andrew; Saltuklaroglu, Tim; Harkrider, Ashley; Cuellar, Megan
2013-01-01
Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.). Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80-100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB. ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDR<.05) suppression in the traditional beta frequency range (13-30 Hz) prior to, during, and following syllable discrimination trials. No significant differences from baseline were found for passive tasks. Tone conditions produced right µ beta suppression following stimulus onset only. For the left µ, significant differences in the magnitude of beta suppression were found for correct speech discrimination trials relative to chance trials following stimulus offset. Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues
Bowers, Andrew; Saltuklaroglu, Tim; Harkrider, Ashley; Cuellar, Megan
2013-01-01
Background Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.) Methods Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80–100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB. Results ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDR<.05) suppression in the traditional beta frequency range (13–30 Hz) prior to, during, and following syllable discrimination trials. No significant differences from baseline were found for passive tasks. Tone conditions produced right µ beta suppression following stimulus onset only. For the left µ, significant differences in the magnitude of beta suppression were found for correct speech discrimination trials relative to chance trials following stimulus offset. Conclusions Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then
Four-Channel Biosignal Analysis and Feature Extraction for Automatic Emotion Recognition
NASA Astrophysics Data System (ADS)
Kim, Jonghwa; André, Elisabeth
This paper investigates the potential of physiological signals as a reliable channel for automatic recognition of user's emotial state. For the emotion recognition, little attention has been paid so far to physiological signals compared to audio-visual emotion channels such as facial expression or speech. All essential stages of automatic recognition system using biosignals are discussed, from recording physiological dataset up to feature-based multiclass classification. Four-channel biosensors are used to measure electromyogram, electrocardiogram, skin conductivity and respiration changes. A wide range of physiological features from various analysis domains, including time/frequency, entropy, geometric analysis, subband spectra, multiscale entropy, etc., is proposed in order to search the best emotion-relevant features and to correlate them with emotional states. The best features extracted are specified in detail and their effectiveness is proven by emotion recognition results.
Real-time automatic registration in optical surgical navigation
NASA Astrophysics Data System (ADS)
Lin, Qinyong; Yang, Rongqian; Cai, Ken; Si, Xuan; Chen, Xiuwen; Wu, Xiaoming
2016-05-01
An image-guided surgical navigation system requires the improvement of the patient-to-image registration time to enhance the convenience of the registration procedure. A critical step in achieving this aim is performing a fully automatic patient-to-image registration. This study reports on a design of custom fiducial markers and the performance of a real-time automatic patient-to-image registration method using these markers on the basis of an optical tracking system for rigid anatomy. The custom fiducial markers are designed to be automatically localized in both patient and image spaces. An automatic localization method is performed by registering a point cloud sampled from the three dimensional (3D) pedestal model surface of a fiducial marker to each pedestal of fiducial markers searched in image space. A head phantom is constructed to estimate the performance of the real-time automatic registration method under four fiducial configurations. The head phantom experimental results demonstrate that the real-time automatic registration method is more convenient, rapid, and accurate than the manual method. The time required for each registration is approximately 0.1 s. The automatic localization method precisely localizes the fiducial markers in image space. The averaged target registration error for the four configurations is approximately 0.7 mm. The automatic registration performance is independent of the positions relative to the tracking system and the movement of the patient during the operation.
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.
Movallali, Guita; Sajedi, Firoozeh
2014-03-01
The use of the internet as a source of information gathering, self-help and support is becoming increasingly recognized. Parents and professionals of children with hearing impairment have been shown to seek information about different communication approaches online. Cued Speech is a very new approach to Persian speaking pupils. Our aim was to develop a useful website to give related information about Persian Cued Speech to parents and professionals of children with hearing impairment. All Cued Speech websites from different countries that fell within the first ten pages of Google and Yahoo search-engines were assessed. Main subjects and links were studied. All related information was gathered from the websites, textbooks, articles etc. Using a framework that combined several criteria for health-information websites, we developed the Persian Cued Speech website for three distinct audiences (parents, professionals and children). An accurate, complete, accessible and readable resource about Persian Cued Speech for parents and professionals is available now.
Speech intelligibility in noise using throat and acoustic microphones.
Acker-Mills, Barbara E; Houtsma, Adrianus J M; Ahroon, William A
2006-01-01
Helicopter cockpits are very noisy and this noise must be reduced for effective communication. The standard U.S. Army aviation helmet is equipped with a noise-canceling acoustic microphone, but some ambient noise still is transmitted. Throat microphones are not sensitive to air molecule vibrations and thus, transmittal of ambient noise is reduced. It is possible that throat microphones could enhance speech communication in helicopters, but speech intelligibility with the devices must first be assessed. In the current study, speech intelligibility of signals generated by an acoustic microphone, a throat microphone, and by the combined output of the two microphones was assessed using the Modified Rhyme Test (MRT). Stimulus words were recorded in a reverberant chamber with ambient broadband noise intensity at 90 and 106 dBA. Listeners completed the MRT task in the same settings, thus simulating the typical environment of a rotary-wing aircraft. Results show that speech intelligibility is significantly worse for the throat microphone (average percent correct = 55.97) than for the acoustic microphone (average percent correct = 69.70), particularly for the higher noise level. In addition, no benefit is gained by simultaneously using both microphones. A follow-up experiment evaluated different consonants using the Diagnostic Rhyme Test and replicated the MRT results. The current results show that intelligibility using throat microphones is poorer than with the use of boom microphones in noisy and in quiet environments. Therefore, throat microphones are not recommended for use in any situation where fast and accurate speech intelligibility is essential.
Expressive facial animation synthesis by learning speech coarticulation and expression spaces.
Deng, Zhigang; Neumann, Ulrich; Lewis, J P; Kim, Tae-Yong; Bulut, Murtaza; Narayanan, Shrikanth
2006-01-01
Synthesizing expressive facial animation is a very challenging topic within the graphics community. In this paper, we present an expressive facial animation synthesis system enabled by automated learning from facial motion capture data. Accurate 3D motions of the markers on the face of a human subject are captured while he/she recites a predesigned corpus, with specific spoken and visual expressions. We present a novel motion capture mining technique that "learns" speech coarticulation models for diphones and triphones from the recorded data. A Phoneme-Independent Expression Eigenspace (PIEES) that encloses the dynamic expression signals is constructed by motion signal processing (phoneme-based time-warping and subtraction) and Principal Component Analysis (PCA) reduction. New expressive facial animations are synthesized as follows: First, the learned coarticulation models are concatenated to synthesize neutral visual speech according to novel speech input, then a texture-synthesis-based approach is used to generate a novel dynamic expression signal from the PIEES model, and finally the synthesized expression signal is blended with the synthesized neutral visual speech to create the final expressive facial animation. Our experiments demonstrate that the system can effectively synthesize realistic expressive facial animation.
Estimating spatial travel times using automatic vehicle identification data
DOT National Transportation Integrated Search
2001-01-01
Prepared ca. 2001. The paper describes an algorithm that was developed for estimating reliable and accurate average roadway link travel times using Automatic Vehicle Identification (AVI) data. The algorithm presented is unique in two aspects. First, ...
Reed, Amanda C.; Centanni, Tracy M.; Borland, Michael S.; Matney, Chanel J.; Engineer, Crystal T.; Kilgard, Michael P.
2015-01-01
Objectives Hearing loss is a commonly experienced disability in a variety of populations including veterans and the elderly and can often cause significant impairment in the ability to understand spoken language. In this study, we tested the hypothesis that neural and behavioral responses to speech will be differentially impaired in an animal model after two forms of hearing loss. Design Sixteen female Sprague–Dawley rats were exposed to one of two types of broadband noise which was either moderate or intense. In nine of these rats, auditory cortex recordings were taken 4 weeks after noise exposure (NE). The other seven were pretrained on a speech sound discrimination task prior to NE and were then tested on the same task after hearing loss. Results Following intense NE, rats had few neural responses to speech stimuli. These rats were able to detect speech sounds but were no longer able to discriminate between speech sounds. Following moderate NE, rats had reorganized cortical maps and altered neural responses to speech stimuli but were still able to accurately discriminate between similar speech sounds during behavioral testing. Conclusions These results suggest that rats are able to adjust to the neural changes after moderate NE and discriminate speech sounds, but they are not able to recover behavioral abilities after intense NE. Animal models could help clarify the adaptive and pathological neural changes that contribute to speech processing in hearing-impaired populations and could be used to test potential behavioral and pharmacological therapies. PMID:25072238
Improving the speech intelligibility in classrooms
NASA Astrophysics Data System (ADS)
Lam, Choi Ling Coriolanus
One of the major acoustical concerns in classrooms is the establishment of effective verbal communication between teachers and students. Non-optimal acoustical conditions, resulting in reduced verbal communication, can cause two main problems. First, they can lead to reduce learning efficiency. Second, they can also cause fatigue, stress, vocal strain and health problems, such as headaches and sore throats, among teachers who are forced to compensate for poor acoustical conditions by raising their voices. Besides, inadequate acoustical conditions can induce the usage of public address system. Improper usage of such amplifiers or loudspeakers can lead to impairment of students' hearing systems. The social costs of poor classroom acoustics will be large to impair the learning of children. This invisible problem has far reaching implications for learning, but is easily solved. Many researches have been carried out that they have accurately and concisely summarized the research findings on classrooms acoustics. Though, there is still a number of challenging questions remaining unanswered. Most objective indices for speech intelligibility are essentially based on studies of western languages. Even several studies of tonal languages as Mandarin have been conducted, there is much less on Cantonese. In this research, measurements have been done in unoccupied rooms to investigate the acoustical parameters and characteristics of the classrooms. The speech intelligibility tests, which based on English, Mandarin and Cantonese, and the survey were carried out on students aged from 5 years old to 22 years old. It aims to investigate the differences in intelligibility between English, Mandarin and Cantonese of the classrooms in Hong Kong. The significance on speech transmission index (STI) related to Phonetically Balanced (PB) word scores will further be developed. Together with developed empirical relationship between the speech intelligibility in classrooms with the variations
Vocabulary Facilitates Speech Perception in Children With Hearing Aids
Walker, Elizabeth A.; Kirby, Benjamin; McCreery, Ryan W.
2017-01-01
Purpose We examined the effects of vocabulary, lexical characteristics (age of acquisition and phonotactic probability), and auditory access (aided audibility and daily hearing aid [HA] use) on speech perception skills in children with HAs. Method Participants included 24 children with HAs and 25 children with normal hearing (NH), ages 5–12 years. Groups were matched on age, expressive and receptive vocabulary, articulation, and nonverbal working memory. Participants repeated monosyllabic words and nonwords in noise. Stimuli varied on age of acquisition, lexical frequency, and phonotactic probability. Performance in each condition was measured by the signal-to-noise ratio at which the child could accurately repeat 50% of the stimuli. Results Children from both groups with larger vocabularies showed better performance than children with smaller vocabularies on nonwords and late-acquired words but not early-acquired words. Overall, children with HAs showed poorer performance than children with NH. Auditory access was not associated with speech perception for the children with HAs. Conclusions Children with HAs show deficits in sensitivity to phonological structure but appear to take advantage of vocabulary skills to support speech perception in the same way as children with NH. Further investigation is needed to understand the causes of the gap that exists between the overall speech perception abilities of children with HAs and children with NH. PMID:28738138
Strand, Edythe A.; Fourakis, Marios; Jakielski, Kathy J.; Hall, Sheryl D.; Karlsson, Heather B.; Mabie, Heather L.; McSweeny, Jane L.; Tilkens, Christie M.; Wilson, David L.
2017-01-01
Purpose Previous articles in this supplement described rationale for and development of the pause marker (PM), a diagnostic marker of childhood apraxia of speech (CAS), and studies supporting its validity and reliability. The present article assesses the theoretical coherence of the PM with speech processing deficits in CAS. Method PM and other scores were obtained for 264 participants in 6 groups: CAS in idiopathic, neurogenetic, and complex neurodevelopmental disorders; adult-onset apraxia of speech (AAS) consequent to stroke and primary progressive apraxia of speech; and idiopathic speech delay. Results Participants with CAS and AAS had significantly lower scores than typically speaking reference participants and speech delay controls on measures posited to assess representational and transcoding processes. Representational deficits differed between CAS and AAS groups, with support for both underspecified linguistic representations and memory/access deficits in CAS, but for only the latter in AAS. CAS–AAS similarities in the age–sex standardized percentages of occurrence of the most frequent type of inappropriate pauses (abrupt) and significant differences in the standardized occurrence of appropriate pauses were consistent with speech processing findings. Conclusions Results support the hypotheses of core representational and transcoding speech processing deficits in CAS and theoretical coherence of the PM's pause-speech elements with these deficits. PMID:28384751
Shriberg, Lawrence D; Strand, Edythe A; Fourakis, Marios; Jakielski, Kathy J; Hall, Sheryl D; Karlsson, Heather B; Mabie, Heather L; McSweeny, Jane L; Tilkens, Christie M; Wilson, David L
2017-04-14
Previous articles in this supplement described rationale for and development of the pause marker (PM), a diagnostic marker of childhood apraxia of speech (CAS), and studies supporting its validity and reliability. The present article assesses the theoretical coherence of the PM with speech processing deficits in CAS. PM and other scores were obtained for 264 participants in 6 groups: CAS in idiopathic, neurogenetic, and complex neurodevelopmental disorders; adult-onset apraxia of speech (AAS) consequent to stroke and primary progressive apraxia of speech; and idiopathic speech delay. Participants with CAS and AAS had significantly lower scores than typically speaking reference participants and speech delay controls on measures posited to assess representational and transcoding processes. Representational deficits differed between CAS and AAS groups, with support for both underspecified linguistic representations and memory/access deficits in CAS, but for only the latter in AAS. CAS-AAS similarities in the age-sex standardized percentages of occurrence of the most frequent type of inappropriate pauses (abrupt) and significant differences in the standardized occurrence of appropriate pauses were consistent with speech processing findings. Results support the hypotheses of core representational and transcoding speech processing deficits in CAS and theoretical coherence of the PM's pause-speech elements with these deficits.
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…
Semi-automatic knee cartilage segmentation
NASA Astrophysics Data System (ADS)
Dam, Erik B.; Folkesson, Jenny; Pettersen, Paola C.; Christiansen, Claus
2006-03-01
Osteo-Arthritis (OA) is a very common age-related cause of pain and reduced range of motion. A central effect of OA is wear-down of the articular cartilage that otherwise ensures smooth joint motion. Quantification of the cartilage breakdown is central in monitoring disease progression and therefore cartilage segmentation is required. Recent advances allow automatic cartilage segmentation with high accuracy in most cases. However, the automatic methods still fail in some problematic cases. For clinical studies, even if a few failing cases will be averaged out in the overall results, this reduces the mean accuracy and precision and thereby necessitates larger/longer studies. Since the severe OA cases are often most problematic for the automatic methods, there is even a risk that the quantification will introduce a bias in the results. Therefore, interactive inspection and correction of these problematic cases is desirable. For diagnosis on individuals, this is even more crucial since the diagnosis will otherwise simply fail. We introduce and evaluate a semi-automatic cartilage segmentation method combining an automatic pre-segmentation with an interactive step that allows inspection and correction. The automatic step consists of voxel classification based on supervised learning. The interactive step combines a watershed transformation of the original scan with the posterior probability map from the classification step at sub-voxel precision. We evaluate the method for the task of segmenting the tibial cartilage sheet from low-field magnetic resonance imaging (MRI) of knees. The evaluation shows that the combined method allows accurate and highly reproducible correction of the segmentation of even the worst cases in approximately ten minutes of interaction.
A Window into the Intoxicated Mind? Speech as an Index of Psychoactive Drug Effects
Bedi, Gillinder; Cecchi, Guillermo A; Slezak, Diego F; Carrillo, Facundo; Sigman, Mariano; de Wit, Harriet
2014-01-01
Abused drugs can profoundly alter mental states in ways that may motivate drug use. These effects are usually assessed with self-report, an approach that is vulnerable to biases. Analyzing speech during intoxication may present a more direct, objective measure, offering a unique ‘window' into the mind. Here, we employed computational analyses of speech semantic and topological structure after ±3,4-methylenedioxymethamphetamine (MDMA; ‘ecstasy') and methamphetamine in 13 ecstasy users. In 4 sessions, participants completed a 10-min speech task after MDMA (0.75 and 1.5 mg/kg), methamphetamine (20 mg), or placebo. Latent Semantic Analyses identified the semantic proximity between speech content and concepts relevant to drug effects. Graph-based analyses identified topological speech characteristics. Group-level drug effects on semantic distances and topology were assessed. Machine-learning analyses (with leave-one-out cross-validation) assessed whether speech characteristics could predict drug condition in the individual subject. Speech after MDMA (1.5 mg/kg) had greater semantic proximity than placebo to the concepts friend, support, intimacy, and rapport. Speech on MDMA (0.75 mg/kg) had greater proximity to empathy than placebo. Conversely, speech on methamphetamine was further from compassion than placebo. Classifiers discriminated between MDMA (1.5 mg/kg) and placebo with 88% accuracy, and MDMA (1.5 mg/kg) and methamphetamine with 84% accuracy. For the two MDMA doses, the classifier performed at chance. These data suggest that automated semantic speech analyses can capture subtle alterations in mental state, accurately discriminating between drugs. The findings also illustrate the potential for automated speech-based approaches to characterize clinically relevant alterations to mental state, including those occurring in psychiatric illness. PMID:24694926
Automatic tracking of labeled red blood cells in microchannels.
Pinho, Diana; Lima, Rui; Pereira, Ana I; Gayubo, Fernando
2013-09-01
The current study proposes an automatic method for the segmentation and tracking of red blood cells flowing through a 100- μm glass capillary. The original images were obtained by means of a confocal system and then processed in MATLAB using the Image Processing Toolbox. The measurements obtained with the proposed automatic method were compared with the results determined by a manual tracking method. The comparison was performed by using both linear regressions and Bland-Altman analysis. The results have shown a good agreement between the two methods. Therefore, the proposed automatic method is a powerful way to provide rapid and accurate measurements for in vitro blood experiments in microchannels. Copyright © 2012 John Wiley & Sons, Ltd.
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
Prosody's Contribution to Fluency: An Examination of the Theory of Automatic Information Processing
ERIC Educational Resources Information Center
Schrauben, Julie E.
2010-01-01
LaBerge and Samuels' (1974) theory of automatic information processing in reading offers a model that explains how and where the processing of information occurs and the degree to which processing of information occurs. These processes are dependent upon two criteria: accurate word decoding and automatic word recognition. However, LaBerge and…
Speech Perception and Short-Term Memory Deficits in Persistent Developmental Speech Disorder
ERIC Educational Resources Information Center
Kenney, Mary Kay; Barac-Cikoja, Dragana; Finnegan, Kimberly; Jeffries, Neal; Ludlow, Christy L.
2006-01-01
Children with developmental speech disorders may have additional deficits in speech perception and/or short-term memory. To determine whether these are only transient developmental delays that can accompany the disorder in childhood or persist as part of the speech disorder, adults with a persistent familial speech disorder were tested on speech…
Magnotti, John F; Beauchamp, Michael S
2017-02-01
Audiovisual speech integration combines information from auditory speech (talker's voice) and visual speech (talker's mouth movements) to improve perceptual accuracy. However, if the auditory and visual speech emanate from different talkers, integration decreases accuracy. Therefore, a key step in audiovisual speech perception is deciding whether auditory and visual speech have the same source, a process known as causal inference. A well-known illusion, the McGurk Effect, consists of incongruent audiovisual syllables, such as auditory "ba" + visual "ga" (AbaVga), that are integrated to produce a fused percept ("da"). This illusion raises two fundamental questions: first, given the incongruence between the auditory and visual syllables in the McGurk stimulus, why are they integrated; and second, why does the McGurk effect not occur for other, very similar syllables (e.g., AgaVba). We describe a simplified model of causal inference in multisensory speech perception (CIMS) that predicts the perception of arbitrary combinations of auditory and visual speech. We applied this model to behavioral data collected from 60 subjects perceiving both McGurk and non-McGurk incongruent speech stimuli. The CIMS model successfully predicted both the audiovisual integration observed for McGurk stimuli and the lack of integration observed for non-McGurk stimuli. An identical model without causal inference failed to accurately predict perception for either form of incongruent speech. The CIMS model uses causal inference to provide a computational framework for studying how the brain performs one of its most important tasks, integrating auditory and visual speech cues to allow us to communicate with others.
Plasticity in the Human Speech Motor System Drives Changes in Speech Perception
Lametti, Daniel R.; Rochet-Capellan, Amélie; Neufeld, Emily; Shiller, Douglas M.
2014-01-01
Recent studies of human speech motor learning suggest that learning is accompanied by changes in auditory perception. But what drives the perceptual change? Is it a consequence of changes in the motor system? Or is it a result of sensory inflow during learning? Here, subjects participated in a speech motor-learning task involving adaptation to altered auditory feedback and they were subsequently tested for perceptual change. In two separate experiments, involving two different auditory perceptual continua, we show that changes in the speech motor system that accompany learning drive changes in auditory speech perception. Specifically, we obtained changes in speech perception when adaptation to altered auditory feedback led to speech production that fell into the phonetic range of the speech perceptual tests. However, a similar change in perception was not observed when the auditory feedback that subjects' received during learning fell into the phonetic range of the perceptual tests. This indicates that the central motor outflow associated with vocal sensorimotor adaptation drives changes to the perceptual classification of speech sounds. PMID:25080594
Parrell, Benjamin; Agnew, Zarinah; Nagarajan, Srikantan; Houde, John; Ivry, Richard B
2017-09-20
The cerebellum has been hypothesized to form a crucial part of the speech motor control network. Evidence for this comes from patients with cerebellar damage, who exhibit a variety of speech deficits, as well as imaging studies showing cerebellar activation during speech production in healthy individuals. To date, the precise role of the cerebellum in speech motor control remains unclear, as it has been implicated in both anticipatory (feedforward) and reactive (feedback) control. Here, we assess both anticipatory and reactive aspects of speech motor control, comparing the performance of patients with cerebellar degeneration and matched controls. Experiment 1 tested feedforward control by examining speech adaptation across trials in response to a consistent perturbation of auditory feedback. Experiment 2 tested feedback control, examining online corrections in response to inconsistent perturbations of auditory feedback. Both male and female patients and controls were tested. The patients were impaired in adapting their feedforward control system relative to controls, exhibiting an attenuated anticipatory response to the perturbation. In contrast, the patients produced even larger compensatory responses than controls, suggesting an increased reliance on sensory feedback to guide speech articulation in this population. Together, these results suggest that the cerebellum is crucial for maintaining accurate feedforward control of speech, but relatively uninvolved in feedback control. SIGNIFICANCE STATEMENT Speech motor control is a complex activity that is thought to rely on both predictive, feedforward control as well as reactive, feedback control. While the cerebellum has been shown to be part of the speech motor control network, its functional contribution to feedback and feedforward control remains controversial. Here, we use real-time auditory perturbations of speech to show that patients with cerebellar degeneration are impaired in adapting feedforward control of
Agnew, Zarinah; Nagarajan, Srikantan; Houde, John; Ivry, Richard B.
2017-01-01
The cerebellum has been hypothesized to form a crucial part of the speech motor control network. Evidence for this comes from patients with cerebellar damage, who exhibit a variety of speech deficits, as well as imaging studies showing cerebellar activation during speech production in healthy individuals. To date, the precise role of the cerebellum in speech motor control remains unclear, as it has been implicated in both anticipatory (feedforward) and reactive (feedback) control. Here, we assess both anticipatory and reactive aspects of speech motor control, comparing the performance of patients with cerebellar degeneration and matched controls. Experiment 1 tested feedforward control by examining speech adaptation across trials in response to a consistent perturbation of auditory feedback. Experiment 2 tested feedback control, examining online corrections in response to inconsistent perturbations of auditory feedback. Both male and female patients and controls were tested. The patients were impaired in adapting their feedforward control system relative to controls, exhibiting an attenuated anticipatory response to the perturbation. In contrast, the patients produced even larger compensatory responses than controls, suggesting an increased reliance on sensory feedback to guide speech articulation in this population. Together, these results suggest that the cerebellum is crucial for maintaining accurate feedforward control of speech, but relatively uninvolved in feedback control. SIGNIFICANCE STATEMENT Speech motor control is a complex activity that is thought to rely on both predictive, feedforward control as well as reactive, feedback control. While the cerebellum has been shown to be part of the speech motor control network, its functional contribution to feedback and feedforward control remains controversial. Here, we use real-time auditory perturbations of speech to show that patients with cerebellar degeneration are impaired in adapting feedforward control of
Speech Perception and Short Term Memory Deficits in Persistent Developmental Speech Disorder
Kenney, Mary Kay; Barac-Cikoja, Dragana; Finnegan, Kimberly; Jeffries, Neal; Ludlow, Christy L.
2008-01-01
Children with developmental speech disorders may have additional deficits in speech perception and/or short-term memory. To determine whether these are only transient developmental delays that can accompany the disorder in childhood or persist as part of the speech disorder, adults with a persistent familial speech disorder were tested on speech perception and short-term memory. Nine adults with a persistent familial developmental speech disorder without language impairment were compared with 20 controls on tasks requiring the discrimination of fine acoustic cues for word identification and on measures of verbal and nonverbal short-term memory. Significant group differences were found in the slopes of the discrimination curves for first formant transitions for word identification with stop gaps of 40 and 20 ms with effect sizes of 1.60 and 1.56. Significant group differences also occurred on tests of nonverbal rhythm and tonal memory, and verbal short-term memory with effect sizes of 2.38, 1.56 and 1.73. No group differences occurred in the use of stop gap durations for word identification. Because frequency-based speech perception and short-term verbal and nonverbal memory deficits both persisted into adulthood in the speech-impaired adults, these deficits may be involved in the persistence of speech disorders without language impairment. PMID:15896836
Careers in Speech Communication.
ERIC Educational Resources Information Center
Speech Communication Association, New York, NY.
Brief discussions in this pamphlet suggest educational and career opportunities in the following fields of speech communication: rhetoric, public address, and communication; theatre, drama, and oral interpretation; radio, television, and film; speech pathology and audiology; speech science, phonetics, and linguistics; and speech education.…
Davidow, Jason H
2014-01-01
Metronome-paced speech results in the elimination, or substantial reduction, of stuttering moments. The cause of fluency during this fluency-inducing condition is unknown. Several investigations have reported changes in speech pattern characteristics from a control condition to a metronome-paced speech condition, but failure to control speech rate between conditions limits our ability to determine if the changes were necessary for fluency. This study examined the effect of speech rate on several speech production variables during one-syllable-per-beat metronomic speech in order to determine changes that may be important for fluency during this fluency-inducing condition. Thirteen persons who stutter (PWS), aged 18-62 years, completed a series of speaking tasks. Several speech production variables were compared between conditions produced at different metronome beat rates, and between a control condition and a metronome-paced speech condition produced at a rate equal to the control condition. Vowel duration, voice onset time, pressure rise time and phonated intervals were significantly impacted by metronome beat rate. Voice onset time and the percentage of short (30-100 ms) phonated intervals significantly decreased from the control condition to the equivalent rate metronome-paced speech condition. A reduction in the percentage of short phonated intervals may be important for fluency during syllable-based metronome-paced speech for PWS. Future studies should continue examining the necessity of this reduction. In addition, speech rate must be controlled in future fluency-inducing condition studies, including neuroimaging investigations, in order for this research to make a substantial contribution to finding the fluency-inducing mechanism of fluency-inducing conditions. © 2013 Royal College of Speech and Language Therapists.
EMG-based speech recognition using hidden markov models with global control variables.
Lee, Ki-Seung
2008-03-01
It is well known that a strong relationship exists between human voices and the movement of articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The sequence of EMG signals for each word is modelled by a hidden Markov model (HMM) framework. The main objective of the work involves building a model for state observation density when multichannel observation sequences are given. The proposed model reflects the dependencies between each of the EMG signals, which are described by introducing a global control variable. We also develop an efficient model training method, based on a maximum likelihood criterion. In a preliminary study, 60 isolated words were used as recognition variables. EMG signals were acquired from three articulatory facial muscles. The findings indicate that such a system may have the capacity to recognize speech signals with an accuracy of up to 87.07%, which is superior to the independent probabilistic model.
Drijvers, Linda; Özyürek, Asli
2017-01-01
This study investigated whether and to what extent iconic co-speech gestures contribute to information from visible speech to enhance degraded speech comprehension at different levels of noise-vocoding. Previous studies of the contributions of these 2 visual articulators to speech comprehension have only been performed separately. Twenty participants watched videos of an actress uttering an action verb and completed a free-recall task. The videos were presented in 3 speech conditions (2-band noise-vocoding, 6-band noise-vocoding, clear), 3 multimodal conditions (speech + lips blurred, speech + visible speech, speech + visible speech + gesture), and 2 visual-only conditions (visible speech, visible speech + gesture). Accuracy levels were higher when both visual articulators were present compared with 1 or none. The enhancement effects of (a) visible speech, (b) gestural information on top of visible speech, and (c) both visible speech and iconic gestures were larger in 6-band than 2-band noise-vocoding or visual-only conditions. Gestural enhancement in 2-band noise-vocoding did not differ from gestural enhancement in visual-only conditions. When perceiving degraded speech in a visual context, listeners benefit more from having both visual articulators present compared with 1. This benefit was larger at 6-band than 2-band noise-vocoding, where listeners can benefit from both phonological cues from visible speech and semantic cues from iconic gestures to disambiguate speech.
Noise and pitch interact during the cortical segregation of concurrent speech.
Bidelman, Gavin M; Yellamsetty, Anusha
2017-08-01
Behavioral studies reveal listeners exploit intrinsic differences in voice fundamental frequency (F0) to segregate concurrent speech sounds-the so-called "F0-benefit." More favorable signal-to-noise ratio (SNR) in the environment, an extrinsic acoustic factor, similarly benefits the parsing of simultaneous speech. Here, we examined the neurobiological substrates of these two cues in the perceptual segregation of concurrent speech mixtures. We recorded event-related brain potentials (ERPs) while listeners performed a speeded double-vowel identification task. Listeners heard two concurrent vowels whose F0 differed by zero or four semitones presented in either clean (no noise) or noise-degraded (+5 dB SNR) conditions. Behaviorally, listeners were more accurate in correctly identifying both vowels for larger F0 separations but F0-benefit was more pronounced at more favorable SNRs (i.e., pitch × SNR interaction). Analysis of the ERPs revealed that only the P2 wave (∼200 ms) showed a similar F0 x SNR interaction as behavior and was correlated with listeners' perceptual F0-benefit. Neural classifiers applied to the ERPs further suggested that speech sounds are segregated neurally within 200 ms based on SNR whereas segregation based on pitch occurs later in time (400-700 ms). The earlier timing of extrinsic SNR compared to intrinsic F0-based segregation implies that the cortical extraction of speech from noise is more efficient than differentiating speech based on pitch cues alone, which may recruit additional cortical processes. Findings indicate that noise and pitch differences interact relatively early in cerebral cortex and that the brain arrives at the identities of concurrent speech mixtures as early as ∼200 ms. Copyright © 2017 Elsevier B.V. All rights reserved.
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.
Speech recognition features for EEG signal description in detection of neonatal seizures.
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.
Obermeier, Christian; Holle, Henning; Gunter, Thomas C
2011-07-01
The present series of experiments explores several issues related to gesture-speech integration and synchrony during sentence processing. To be able to more precisely manipulate gesture-speech synchrony, we used gesture fragments instead of complete gestures, thereby avoiding the usual long temporal overlap of gestures with their coexpressive speech. In a pretest, the minimal duration of an iconic gesture fragment needed to disambiguate a homonym (i.e., disambiguation point) was therefore identified. In three subsequent ERP experiments, we then investigated whether the gesture information available at the disambiguation point has immediate as well as delayed consequences on the processing of a temporarily ambiguous spoken sentence, and whether these gesture-speech integration processes are susceptible to temporal synchrony. Experiment 1, which used asynchronous stimuli as well as an explicit task, showed clear N400 effects at the homonym as well as at the target word presented further downstream, suggesting that asynchrony does not prevent integration under explicit task conditions. No such effects were found when asynchronous stimuli were presented using a more shallow task (Experiment 2). Finally, when gesture fragment and homonym were synchronous, similar results as in Experiment 1 were found, even under shallow task conditions (Experiment 3). We conclude that when iconic gesture fragments and speech are in synchrony, their interaction is more or less automatic. When they are not, more controlled, active memory processes are necessary to be able to combine the gesture fragment and speech context in such a way that the homonym is disambiguated correctly.
ERIC Educational Resources Information Center
Hamade, Rachel; Hewlett, Nigel; Scanlon, Emer
2006-01-01
This study aimed to evaluate a new automatic tracheostoma valve: the Provox FreeHands HME (manufactured by Atos Medical AB, Sweden). Data from four laryngectomee participants using automatic and also manual occlusion were subjected to acoustic and perceptual analysis. The main results were a significant decrease, from the manual to automatic…
The role of temporal speech cues in facilitating the fluency of adults who stutter.
Park, Jin; Logan, Kenneth J
2015-12-01
Adults who stutter speak more fluently during choral speech contexts than they do during solo speech contexts. The underlying mechanisms for this effect remain unclear, however. In this study, we examined the extent to which the choral speech effect depended on presentation of intact temporal speech cues. We also examined whether speakers who stutter followed choral signals more closely than typical speakers did. 8 adults who stuttered and 8 adults who did not stutter read 60 sentences aloud during a solo speaking condition and three choral speaking conditions (240 total sentences), two of which featured either temporally altered or indeterminate word duration patterns. Effects of these manipulations on speech fluency, rate, and temporal entrainment with the choral speech signal were assessed. Adults who stutter spoke more fluently in all choral speaking conditions than they did when speaking solo. They also spoke slower and exhibited closer temporal entrainment with the choral signal during the mid- to late-stages of sentence production than the adults who did not stutter. Both groups entrained more closely with unaltered choral signals than they did with altered choral signals. Findings suggest that adults who stutter make greater use of speech-related information in choral signals when talking than adults with typical fluency do. The presence of fluency facilitation during temporally altered choral speech and conversation babble, however, suggests that temporal/gestural cueing alone cannot account for fluency facilitation in speakers who stutter. Other potential fluency enhancing mechanisms are discussed. The reader will be able to (a) summarize competing views on stuttering as a speech timing disorder, (b) describe the extent to which adults who stutter depend on an accurate rendering of temporal information in order to benefit from choral speech, and (c) discuss possible explanations for fluency facilitation in the presence of inaccurate or indeterminate
Measures of voiced frication for automatic classification
NASA Astrophysics Data System (ADS)
Jackson, Philip J. B.; Jesus, Luis M. T.; Shadle, Christine H.; Pincas, Jonathan
2004-05-01
As an approach to understanding the characteristics of the acoustic sources in voiced fricatives, it seems apt to draw on knowledge of vowels and voiceless fricatives, which have been relatively well studied. However, the presence of both phonation and frication in these mixed-source sounds offers the possibility of mutual interaction effects, with variations across place of articulation. This paper examines the acoustic and articulatory consequences of these interactions and explores automatic techniques for finding parametric and statistical descriptions of these phenomena. A reliable and consistent set of such acoustic cues could be used for phonetic classification or speech recognition. Following work on devoicing of European Portuguese voiced fricatives [Jesus and Shadle, in Mamede et al. (eds.) (Springer-Verlag, Berlin, 2003), pp. 1-8]. and the modulating effect of voicing on frication [Jackson and Shadle, J. Acoust. Soc. Am. 108, 1421-1434 (2000)], the present study focuses on three types of information: (i) sequences and durations of acoustic events in VC transitions, (ii) temporal, spectral and modulation measures from the periodic and aperiodic components of the acoustic signal, and (iii) voicing activity derived from simultaneous EGG data. Analysis of interactions observed in British/American English and European Portuguese speech corpora will be compared, and the principal findings discussed.
Russell, Ginny; Miller, Laura L; Ford, Tamsin; Golding, Jean
2014-01-01
Retrospective recall about children's symptoms is used to establish early developmental patterns in clinical practice and is also utilised in child psychopathology research. Some studies have indicated that the accuracy of retrospective recall is influenced by life events. Our hypothesis was that an intervention: speech and language therapy, would adversely affect the accuracy of parent recall of early concerns about their child's speech and language development. Mothers (n = 5,390) reported on their child's speech development (child male to female ratio = 50:50) when their children were aged 18 or 30 months, and also reported on these early concerns retrospectively, 10 years later, when their children were 13 years old. Overall reliability of retrospective recall was good, 86 % of respondents accurately recalling their earlier concerns. As hypothesised, however, the speech and language intervention was strongly associated with inaccurate retrospective recall about concerns in the early years (Relative Risk Ratio = 19.03; 95 % CI:14.78-24.48). Attendance at speech therapy was associated with increased recall of concerns that were not reported at the time. The study suggests caution is required when interpreting retrospective reports of abnormal child development as recall may be influenced by intervening events.
End-to-End ASR-Free Keyword Search From Speech
NASA Astrophysics Data System (ADS)
Audhkhasi, Kartik; Rosenberg, Andrew; Sethy, Abhinav; Ramabhadran, Bhuvana; Kingsbury, Brian
2017-12-01
End-to-end (E2E) systems have achieved competitive results compared to conventional hybrid hidden Markov model (HMM)-deep neural network based automatic speech recognition (ASR) systems. Such E2E systems are attractive due to the lack of dependence on alignments between input acoustic and output grapheme or HMM state sequence during training. This paper explores the design of an ASR-free end-to-end system for text query-based keyword search (KWS) from speech trained with minimal supervision. Our E2E KWS system consists of three sub-systems. The first sub-system is a recurrent neural network (RNN)-based acoustic auto-encoder trained to reconstruct the audio through a finite-dimensional representation. The second sub-system is a character-level RNN language model using embeddings learned from a convolutional neural network. Since the acoustic and text query embeddings occupy different representation spaces, they are input to a third feed-forward neural network that predicts whether the query occurs in the acoustic utterance or not. This E2E ASR-free KWS system performs respectably despite lacking a conventional ASR system and trains much faster.
The Role of Visual Speech Information in Supporting Perceptual Learning of Degraded Speech
ERIC Educational Resources Information Center
Wayne, Rachel V.; Johnsrude, Ingrid S.
2012-01-01
Following cochlear implantation, hearing-impaired listeners must adapt to speech as heard through their prosthesis. Visual speech information (VSI; the lip and facial movements of speech) is typically available in everyday conversation. Here, we investigate whether learning to understand a popular auditory simulation of speech as transduced by a…
Digitized Speech Characteristics in Patients with Maxillectomy Defects.
Elbashti, Mahmoud E; Sumita, Yuka I; Hattori, Mariko; Aswehlee, Amel M; Taniguchi, Hisashi
2017-12-06
Accurate evaluation of speech characteristics through formant frequency measurement is important for proper speech rehabilitation in patients after maxillectomy. This study aimed to evaluate the utility of digital acoustic analysis and vowel pentagon space for the prediction of speech ability after maxillectomy, by comparing the acoustic characteristics of vowel articulation in three classes of maxillectomy defects. Aramany's classifications I, II, and IV were used to group 27 male patients after maxillectomy. Digital acoustic analysis of five Japanese vowels-/a/, /e/, /i/, /o/, and /u/-was performed using a speech analysis system. First formant (F1) and second formant (F2) frequencies were calculated using an autocorrelation method. Data were plotted on an F1-F2 plane for each patient, and the F1 and F2 ranges were calculated. The vowel pentagon spaces were also determined. One-way ANOVA was applied to compare all results between the three groups. Class II maxillectomy patients had a significantly higher F2 range than did Class I and Class IV patients (p = 0.002). In contrast, there was no significant difference in the F1 range between the three classes. The vowel pentagon spaces were significantly larger in class II maxillectomy patients than in Class I and Class IV patients (p = 0.014). The results of this study indicate that the acoustic characteristics of maxillectomy patients are affected by the defect area. This finding may provide information for obturator design based on vowel articulation and defect class. © 2017 by the American College of Prosthodontists.
ERIC Educational Resources Information Center
Davidow, Jason H.; Ingham, Roger J.
2013-01-01
Purpose: This study examined the effect of speech rate on phonated intervals (PIs), in order to test whether a reduction in the frequency of short PIs is an important part of the fluency-inducing mechanism of chorus reading. The influence of speech rate on stuttering frequency, speaker-judged speech effort, and listener-judged naturalness was also…
ERIC Educational Resources Information Center
Iuzzini-Seigel, Jenya; Hogan, Tiffany P.; Green, Jordan R.
2017-01-01
Purpose: The current research sought to determine (a) if speech inconsistency is a core feature of childhood apraxia of speech (CAS) or if it is driven by comorbid language impairment that affects a large subset of children with CAS and (b) if speech inconsistency is a sensitive and specific diagnostic marker that can differentiate between CAS and…
Davidow, Jason H.
2013-01-01
Background Metronome-paced speech results in the elimination, or substantial reduction, of stuttering moments. The cause of fluency during this fluency-inducing condition is unknown. Several investigations have reported changes in speech pattern characteristics from a control condition to a metronome-paced speech condition, but failure to control speech rate between conditions limits our ability to determine if the changes were necessary for fluency. Aims This study examined the effect of speech rate on several speech production variables during one-syllable-per-beat metronomic speech, in order to determine changes that may be important for fluency during this fluency-inducing condition. Methods and Procedures Thirteen persons who stutter (PWS), aged 18–62 years, completed a series of speaking tasks. Several speech production variables were compared between conditions produced at different metronome beat rates, and between a control condition and a metronome-paced speech condition produced at a rate equal to the control condition. Outcomes & Results Vowel duration, voice onset time, pressure rise time, and phonated intervals were significantly impacted by metronome beat rate. Voice onset time and the percentage of short (30–100 ms) phonated intervals significantly decreased from the control condition to the equivalent rate metronome-paced speech condition. Conclusions & Implications A reduction in the percentage of short phonated intervals may be important for fluency during syllable-based metronome-paced speech for PWS. Future studies should continue examining the necessity of this reduction. In addition, speech rate must be controlled in future fluency-inducing condition studies, including neuroimaging investigations, in order for this research to make a substantial contribution to finding the fluency-inducing mechanism of fluency-inducing conditions. PMID:24372888
Children with bilateral cochlear implants identify emotion in speech and music.
Volkova, Anna; Trehub, Sandra E; Schellenberg, E Glenn; Papsin, Blake C; Gordon, Karen A
2013-03-01
This study examined the ability of prelingually deaf children with bilateral implants to identify emotion (i.e. happiness or sadness) in speech and music. Participants in Experiment 1 were 14 prelingually deaf children from 5-7 years of age who had bilateral implants and 18 normally hearing children from 4-6 years of age. They judged whether linguistically neutral utterances produced by a man and woman sounded happy or sad. Participants in Experiment 2 were 14 bilateral implant users from 4-6 years of age and the same normally hearing children as in Experiment 1. They judged whether synthesized piano excerpts sounded happy or sad. Child implant users' accuracy of identifying happiness and sadness in speech was well above chance levels but significantly below the accuracy achieved by children with normal hearing. Similarly, their accuracy of identifying happiness and sadness in music was well above chance levels but significantly below that of children with normal hearing, who performed at ceiling. For the 12 implant users who participated in both experiments, performance on the speech task correlated significantly with performance on the music task and implant experience was correlated with performance on both tasks. Child implant users' accurate identification of emotion in speech exceeded performance in previous studies, which may be attributable to fewer response alternatives and the use of child-directed speech. Moreover, child implant users' successful identification of emotion in music indicates that the relevant cues are accessible at a relatively young age.
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.
Segregation of Whispered Speech Interleaved with Noise or Speech Maskers
2011-08-01
range over which the talker can be heard. Whispered speech is produced by modulating the flow of air through partially open vocal folds. Because the...source of excitation is turbulent air flow , the acoustic characteristics of whispered speech differs from voiced speech [1, 2]. Despite the acoustic...signals provided by cochlear implants. Two studies investigated the segregation of simultaneously presented whispered vowels [7, 8] in a standard
Subband-Based Group Delay Segmentation of Spontaneous Speech into Syllable-Like Units
NASA Astrophysics Data System (ADS)
Nagarajan, T.; Murthy, H. A.
2004-12-01
In the development of a syllable-centric automatic speech recognition (ASR) system, segmentation of the acoustic signal into syllabic units is an important stage. Although the short-term energy (STE) function contains useful information about syllable segment boundaries, it has to be processed before segment boundaries can be extracted. This paper presents a subband-based group delay approach to segment spontaneous speech into syllable-like units. This technique exploits the additive property of the Fourier transform phase and the deconvolution property of the cepstrum to smooth the STE function of the speech signal and make it suitable for syllable boundary detection. By treating the STE function as a magnitude spectrum of an arbitrary signal, a minimum-phase group delay function is derived. This group delay function is found to be a better representative of the STE function for syllable boundary detection. Although the group delay function derived from the STE function of the speech signal contains segment boundaries, the boundaries are difficult to determine in the context of long silences, semivowels, and fricatives. In this paper, these issues are specifically addressed and algorithms are developed to improve the segmentation performance. The speech signal is first passed through a bank of three filters, corresponding to three different spectral bands. The STE functions of these signals are computed. Using these three STE functions, three minimum-phase group delay functions are derived. By combining the evidence derived from these group delay functions, the syllable boundaries are detected. Further, a multiresolution-based technique is presented to overcome the problem of shift in segment boundaries during smoothing. Experiments carried out on the Switchboard and OGI-MLTS corpora show that the error in segmentation is at most 25 milliseconds for 67% and 76.6% of the syllable segments, respectively.
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.
Audiovisual Temporal Recalibration for Speech in Synchrony Perception and Speech Identification
NASA Astrophysics Data System (ADS)
Asakawa, Kaori; Tanaka, Akihiro; Imai, Hisato
We investigated whether audiovisual synchrony perception for speech could change after observation of the audiovisual temporal mismatch. Previous studies have revealed that audiovisual synchrony perception is re-calibrated after exposure to a constant timing difference between auditory and visual signals in non-speech. In the present study, we examined whether this audiovisual temporal recalibration occurs at the perceptual level even for speech (monosyllables). In Experiment 1, participants performed an audiovisual simultaneity judgment task (i.e., a direct measurement of the audiovisual synchrony perception) in terms of the speech signal after observation of the speech stimuli which had a constant audiovisual lag. The results showed that the “simultaneous” responses (i.e., proportion of responses for which participants judged the auditory and visual stimuli to be synchronous) at least partly depended on exposure lag. In Experiment 2, we adopted the McGurk identification task (i.e., an indirect measurement of the audiovisual synchrony perception) to exclude the possibility that this modulation of synchrony perception was solely attributable to the response strategy using stimuli identical to those of Experiment 1. The characteristics of the McGurk effect reported by participants depended on exposure lag. Thus, it was shown that audiovisual synchrony perception for speech could be modulated following exposure to constant lag both in direct and indirect measurement. Our results suggest that temporal recalibration occurs not only in non-speech signals but also in monosyllabic speech at the perceptual level.
Speeches Archive Former AF Top 3 Viewpoints and Speeches Air Force Warrior Games 2017 Events 2018 Air Force Strategic Documents Desert Storm 25th Anniversary Observances DoD Warrior Games Portraits in Courage
Keller, M David; Ziriax, John M; Barns, William; Sheffield, Benjamin; Brungart, Douglas; Thomas, Tony; Jaeger, Bobby; Yankaskas, Kurt
2017-06-01
Noise, hearing loss, and electronic signal distortion, which are common problems in military environments, can impair speech intelligibility and thereby jeopardize mission success. The current study investigated the impact that impaired communication has on operational performance in a command and control environment by parametrically degrading speech intelligibility in a simulated shipborne Combat Information Center. Experienced U.S. Navy personnel served as the study participants and were required to monitor information from multiple sources and respond appropriately to communications initiated by investigators playing the roles of other personnel involved in a realistic Naval scenario. In each block of the scenario, an adaptive intelligibility modification system employing automatic gain control was used to adjust the signal-to-noise ratio to achieve one of four speech intelligibility levels on a Modified Rhyme Test: No Loss, 80%, 60%, or 40%. Objective and subjective measures of operational performance suggested that performance systematically degraded with decreasing speech intelligibility, with the largest drop occurring between 80% and 60%. These results confirm the importance of noise reduction, good communication design, and effective hearing conservation programs to maximize the operational effectiveness of military personnel. Published by Elsevier B.V.
ERIC Educational Resources Information Center
Harkins, Judith E., Ed.; Virvan, Barbara M., Ed.
The conference proceedings contains 23 papers on telephone relay service, real-time captioning, and automatic speech recognition, and a glossary. The keynote address, by Representative Major R. Owens, examines current issues in federal legislation. Other papers have the following titles and authors: "Telephone Relay Service: Rationale and…
Reviewing the connection between speech and obstructive sleep apnea.
Espinoza-Cuadros, Fernando; Fernández-Pozo, Rubén; Toledano, Doroteo T; Alcázar-Ramírez, José D; López-Gonzalo, Eduardo; Hernández-Gómez, Luis A
2016-02-20
Sleep apnea (OSA) is a common sleep disorder characterized by recurring breathing pauses during sleep caused by a blockage of the upper airway (UA). The altered UA structure or function in OSA speakers has led to hypothesize the automatic analysis of speech for OSA assessment. In this paper we critically review several approaches using speech analysis and machine learning techniques for OSA detection, and discuss the limitations that can arise when using machine learning techniques for diagnostic applications. A large speech database including 426 male Spanish speakers suspected to suffer OSA and derived to a sleep disorders unit was used to study the clinical validity of several proposals using machine learning techniques to predict the apnea-hypopnea index (AHI) or classify individuals according to their OSA severity. AHI describes the severity of patients' condition. We first evaluate AHI prediction using state-of-the-art speaker recognition technologies: speech spectral information is modelled using supervectors or i-vectors techniques, and AHI is predicted through support vector regression (SVR). Using the same database we then critically review several OSA classification approaches previously proposed. The influence and possible interference of other clinical variables or characteristics available for our OSA population: age, height, weight, body mass index, and cervical perimeter, are also studied. The poor results obtained when estimating AHI using supervectors or i-vectors followed by SVR contrast with the positive results reported by previous research. This fact prompted us to a careful review of these approaches, also testing some reported results over our database. Several methodological limitations and deficiencies were detected that may have led to overoptimistic results. The methodological deficiencies observed after critically reviewing previous research can be relevant examples of potential pitfalls when using machine learning techniques for
NASA Astrophysics Data System (ADS)
Samardzic, Nikolina
The effectiveness of in-vehicle speech communication can be a good indicator of the perception of the overall vehicle quality and customer satisfaction. Currently available speech intelligibility metrics do not account in their procedures for essential parameters needed for a complete and accurate evaluation of in-vehicle speech intelligibility. These include the directivity and the distance of the talker with respect to the listener, binaural listening, hearing profile of the listener, vocal effort, and multisensory hearing. In the first part of this research the effectiveness of in-vehicle application of these metrics is investigated in a series of studies to reveal their shortcomings, including a wide range of scores resulting from each of the metrics for a given measurement configuration and vehicle operating condition. In addition, the nature of a possible correlation between the scores obtained from each metric is unknown. The metrics and the subjective perception of speech intelligibility using, for example, the same speech material have not been compared in literature. As a result, in the second part of this research, an alternative method for speech intelligibility evaluation is proposed for use in the automotive industry by utilizing a virtual reality driving environment for ultimately setting targets, including the associated statistical variability, for future in-vehicle speech intelligibility evaluation. The Speech Intelligibility Index (SII) was evaluated at the sentence Speech Receptions Threshold (sSRT) for various listening situations and hearing profiles using acoustic perception jury testing and a variety of talker and listener configurations and background noise. In addition, the effect of individual sources and transfer paths of sound in an operating vehicle to the vehicle interior sound, specifically their effect on speech intelligibility was quantified, in the framework of the newly developed speech intelligibility evaluation method. Lastly
... able to assess your child’s speech production and language development and make appropriate therapy recommendations. It is also ... pathologist should consistently assess your child’s speech and language development, as well as screen for hearing problems (with ...
Hate Speech or Free Speech: Can Broad Campus Speech Regulations Survive Current Judicial Reasoning?
ERIC Educational Resources Information Center
Heiser, Gregory M.; Rossow, Lawrence F.
1993-01-01
Federal courts have found speech regulations overbroad in suits against the University of Michigan and the University of Wisconsin System. Attempts to assess the theoretical justification and probable fate of broad speech regulations that have not been explicitly rejected by the courts. Concludes that strong arguments for broader regulation will…
Robust Speech Enhancement Using Two-Stage Filtered Minima Controlled Recursive Averaging
NASA Astrophysics Data System (ADS)
Ghourchian, Negar; Selouani, Sid-Ahmed; O'Shaughnessy, Douglas
In this paper we propose an algorithm for estimating noise in highly non-stationary noisy environments, which is a challenging problem in speech enhancement. This method is based on minima-controlled recursive averaging (MCRA) whereby an accurate, robust and efficient noise power spectrum estimation is demonstrated. We propose a two-stage technique to prevent the appearance of musical noise after enhancement. This algorithm filters the noisy speech to achieve a robust signal with minimum distortion in the first stage. Subsequently, it estimates the residual noise using MCRA and removes it with spectral subtraction. The proposed Filtered MCRA (FMCRA) performance is evaluated using objective tests on the Aurora database under various noisy environments. These measures indicate the higher output SNR and lower output residual noise and distortion.
Speech Recognition for Medical Dictation: Overview in Quebec and Systematic Review.
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.
Automatic analysis for neuron by confocal laser scanning microscope
NASA Astrophysics Data System (ADS)
Satou, Kouhei; Aoki, Yoshimitsu; Mataga, Nobuko; Hensh, Takao K.; Taki, Katuhiko
2005-12-01
The aim of this study is to develop a system that recognizes both the macro- and microscopic configurations of nerve cells and automatically performs the necessary 3-D measurements and functional classification of spines. The acquisition of 3-D images of cranial nerves has been enabled by the use of a confocal laser scanning microscope, although the highly accurate 3-D measurements of the microscopic structures of cranial nerves and their classification based on their configurations have not yet been accomplished. In this study, in order to obtain highly accurate measurements of the microscopic structures of cranial nerves, existing positions of spines were predicted by the 2-D image processing of tomographic images. Next, based on the positions that were predicted on the 2-D images, the positions and configurations of the spines were determined more accurately by 3-D image processing of the volume data. We report the successful construction of an automatic analysis system that uses a coarse-to-fine technique to analyze the microscopic structures of cranial nerves with high speed and accuracy by combining 2-D and 3-D image analyses.
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.
Automatic systems and the low-level wind hazard
NASA Technical Reports Server (NTRS)
Schaeffer, Dwight R.
1987-01-01
Automatic flight control systems provide means for significantly enhancing survivability in severe wind hazards. The technology required to produce the necessary control algorithms is available and has been made technically feasible by the advent of digital flight control systems and accurate, low-noise sensors, especially strap-down inertial sensors. The application of this technology and these means has not generally been enabled except for automatic landing systems, and even then the potential has not been fully exploited. To fully exploit the potential of automatic systems for enhancing safety in wind hazards requires providing incentives, creating demand, inspiring competition, education, and eliminating prejudicial disincentitives to overcome the economic penalties associated with the extensive and riskly development and certification of these systems. If these changes will come about at all, it will likely be through changes in the regulations provided by the certifying agencies.
ERIC Educational Resources Information Center
Jerger, Susan; Damian, Markus F.; McAlpine, Rachel P.; Abdi, Herve
2018-01-01
To communicate, children must discriminate and identify speech sounds. Because visual speech plays an important role in this process, we explored how visual speech influences phoneme discrimination and identification by children. Critical items had intact visual speech (e.g. baez) coupled to non-intact (excised onsets) auditory speech (signified…
... pay for speech therapy for children born with cleft lip and palate, though they may limit the number of therapy ... Hardin-Jones, Karnell (2000). Communicative Disorders Related to Cleft Lip and Palate . Bzoch (1997). Cleft Palate Speech Management: A Multidisciplinary ...
Speech in spinocerebellar ataxia.
Schalling, Ellika; Hartelius, Lena
2013-12-01
Spinocerebellar ataxias (SCAs) are a heterogeneous group of autosomal dominant cerebellar ataxias clinically characterized by progressive ataxia, dysarthria and a range of other concomitant neurological symptoms. Only a few studies include detailed characterization of speech symptoms in SCA. Speech symptoms in SCA resemble ataxic dysarthria but symptoms related to phonation may be more prominent. One study to date has shown an association between differences in speech and voice symptoms related to genotype. More studies of speech and voice phenotypes are motivated, to possibly aid in clinical diagnosis. In addition, instrumental speech analysis has been demonstrated to be a reliable measure that may be used to monitor disease progression or therapy outcomes in possible future pharmacological treatments. Intervention by speech and language pathologists should go beyond assessment. Clinical guidelines for management of speech, communication and swallowing need to be developed for individuals with progressive cerebellar ataxia. Copyright © 2013 Elsevier Inc. All rights reserved.
Discriminating between auditory and motor cortical responses to speech and non-speech mouth sounds
Agnew, Z.K.; McGettigan, C.; Scott, S.K.
2012-01-01
Several perspectives on speech perception posit a central role for the representation of articulations in speech comprehension, supported by evidence for premotor activation when participants listen to speech. However no experiments have directly tested whether motor responses mirror the profile of selective auditory cortical responses to native speech sounds, or whether motor and auditory areas respond in different ways to sounds. We used fMRI to investigate cortical responses to speech and non-speech mouth (ingressive click) sounds. Speech sounds activated bilateral superior temporal gyri more than other sounds, a profile not seen in motor and premotor cortices. These results suggest that there are qualitative differences in the ways that temporal and motor areas are activated by speech and click sounds: anterior temporal lobe areas are sensitive to the acoustic/phonetic properties while motor responses may show more generalised responses to the acoustic stimuli. PMID:21812557
Keilmann, Annerose; Friese, Barbara; Lässig, Anne; Hoffmann, Vanessa
2018-04-01
The introduction of neonatal hearing screening and the increasingly early age at which children can receive a cochlear implant has intensified the need for a validated questionnaire to assess the speech production of children aged 0‒18. Such a questionnaire has been created, the LittlEARS ® Early Speech Production Questionnaire (LEESPQ). This study aimed to validate a second, revised edition of the LEESPQ. Questionnaires were returned for 362 children with normal hearing. Completed questionnaires were analysed to determine if the LEESPQ is reliable, prognostically accurate, internally consistent, and if gender or multilingualism affects total scores. Total scores correlated positively with age. The LEESPQ is reliable, accurate, and consistent, and independent of gender or lingual status. A norm curve was created. This second version of the LEESPQ is a valid tool to assess the speech production development of children with normal hearing, aged 0‒18, regardless of their gender. As such, the LEESPQ may be a useful tool to monitor the development of paediatric hearing device users. The second version of the LEESPQ is a valid instrument for assessing early speech production of children aged 0‒18 months.
Neural-scaled entropy predicts the effects of nonlinear frequency compression on speech perception
Rallapalli, Varsha H.; Alexander, Joshua M.
2015-01-01
The Neural-Scaled Entropy (NSE) model quantifies information in the speech signal that has been altered beyond simple gain adjustments by sensorineural hearing loss (SNHL) and various signal processing. An extension of Cochlear-Scaled Entropy (CSE) [Stilp, Kiefte, Alexander, and Kluender (2010). J. Acoust. Soc. Am. 128(4), 2112–2126], NSE quantifies information as the change in 1-ms neural firing patterns across frequency. To evaluate the model, data from a study that examined nonlinear frequency compression (NFC) in listeners with SNHL were used because NFC can recode the same input information in multiple ways in the output, resulting in different outcomes for different speech classes. Overall, predictions were more accurate for NSE than CSE. The NSE model accurately described the observed degradation in recognition, and lack thereof, for consonants in a vowel-consonant-vowel context that had been processed in different ways by NFC. While NSE accurately predicted recognition of vowel stimuli processed with NFC, it underestimated them relative to a low-pass control condition without NFC. In addition, without modifications, it could not predict the observed improvement in recognition for word final /s/ and /z/. Findings suggest that model modifications that include information from slower modulations might improve predictions across a wider variety of conditions. PMID:26627780
CAD-based Automatic Modeling Method for Geant4 geometry model Through MCAM
NASA Astrophysics Data System (ADS)
Wang, Dong; Nie, Fanzhi; Wang, Guozhong; Long, Pengcheng; LV, Zhongliang; LV, Zhongliang
2014-06-01
Geant4 is a widely used Monte Carlo transport simulation package. Before calculating using Geant4, the calculation model need be established which could be described by using Geometry Description Markup Language (GDML) or C++ language. However, it is time-consuming and error-prone to manually describe the models by GDML. Automatic modeling methods have been developed recently, but there are some problem existed in most of present modeling programs, specially some of them were not accurate or adapted to specifically CAD format. To convert the GDML format models to CAD format accurately, a Geant4 Computer Aided Design (CAD) based modeling method was developed for automatically converting complex CAD geometry model into GDML geometry model. The essence of this method was dealing with CAD model represented with boundary representation (B-REP) and GDML model represented with constructive solid geometry (CSG). At first, CAD model was decomposed to several simple solids which had only one close shell. And then the simple solid was decomposed to convex shell set. Then corresponding GDML convex basic solids were generated by the boundary surfaces getting from the topological characteristic of a convex shell. After the generation of these solids, GDML model was accomplished with series boolean operations. This method was adopted in CAD/Image-based Automatic Modeling Program for Neutronics & Radiation Transport (MCAM), and tested with several models including the examples in Geant4 install package. The results showed that this method could convert standard CAD model accurately, and can be used for Geant4 automatic modeling.
Zamaninezhad, Ladan; Hohmann, Volker; Büchner, Andreas; Schädler, Marc René; Jürgens, Tim
2017-02-01
This study introduces a speech intelligibility model for cochlear implant users with ipsilateral preserved acoustic hearing that aims at simulating the observed speech-in-noise intelligibility benefit when receiving simultaneous electric and acoustic stimulation (EA-benefit). The model simulates the auditory nerve spiking in response to electric and/or acoustic stimulation. The temporally and spatially integrated spiking patterns were used as the final internal representation of noisy speech. Speech reception thresholds (SRTs) in stationary noise were predicted for a sentence test using an automatic speech recognition framework. The model was employed to systematically investigate the effect of three physiologically relevant model factors on simulated SRTs: (1) the spatial spread of the electric field which co-varies with the number of electrically stimulated auditory nerves, (2) the "internal" noise simulating the deprivation of auditory system, and (3) the upper bound frequency limit of acoustic hearing. The model results show that the simulated SRTs increase monotonically with increasing spatial spread for fixed internal noise, and also increase with increasing the internal noise strength for a fixed spatial spread. The predicted EA-benefit does not follow such a systematic trend and depends on the specific combination of the model parameters. Beyond 300 Hz, the upper bound limit for preserved acoustic hearing is less influential on speech intelligibility of EA-listeners in stationary noise. The proposed model-predicted EA-benefits are within the range of EA-benefits shown by 18 out of 21 actual cochlear implant listeners with preserved acoustic hearing. Copyright © 2016 Elsevier B.V. All rights reserved.
Relative Salience of Speech Rhythm and Speech Rate on Perceived Foreign Accent in a Second Language.
Polyanskaya, Leona; Ordin, Mikhail; Busa, Maria Grazia
2017-09-01
We investigated the independent contribution of speech rate and speech rhythm to perceived foreign accent. To address this issue we used a resynthesis technique that allows neutralizing segmental and tonal idiosyncrasies between identical sentences produced by French learners of English at different proficiency levels and maintaining the idiosyncrasies pertaining to prosodic timing patterns. We created stimuli that (1) preserved the idiosyncrasies in speech rhythm while controlling for the differences in speech rate between the utterances; (2) preserved the idiosyncrasies in speech rate while controlling for the differences in speech rhythm between the utterances; and (3) preserved the idiosyncrasies both in speech rate and speech rhythm. All the stimuli were created in intoned (with imposed intonational contour) and flat (with monotonized, constant F0) conditions. The original and the resynthesized sentences were rated by native speakers of English for degree of foreign accent. We found that both speech rate and speech rhythm influence the degree of perceived foreign accent, but the effect of speech rhythm is larger than that of speech rate. We also found that intonation enhances the perception of fine differences in rhythmic patterns but reduces the perceptual salience of fine differences in speech rate.
Non-speech oral motor treatment for children with developmental speech sound disorders.
Lee, Alice S-Y; Gibbon, Fiona E
2015-03-25
Children with developmental speech sound disorders have difficulties in producing the speech sounds of their native language. These speech difficulties could be due to structural, sensory or neurophysiological causes (e.g. hearing impairment), but more often the cause of the problem is unknown. One treatment approach used by speech-language therapists/pathologists is non-speech oral motor treatment (NSOMT). NSOMTs are non-speech activities that aim to stimulate or improve speech production and treat specific speech errors. For example, using exercises such as smiling, pursing, blowing into horns, blowing bubbles, and lip massage to target lip mobility for the production of speech sounds involving the lips, such as /p/, /b/, and /m/. The efficacy of this treatment approach is controversial, and evidence regarding the efficacy of NSOMTs needs to be examined. To assess the efficacy of non-speech oral motor treatment (NSOMT) in treating children with developmental speech sound disorders who have speech errors. In April 2014 we searched the Cochrane Central Register of Controlled Trials (CENTRAL), Ovid MEDLINE (R) and Ovid MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, Education Resources Information Center (ERIC), PsycINFO and 11 other databases. We also searched five trial and research registers, checked the reference lists of relevant titles identified by the search and contacted researchers to identify other possible published and unpublished studies. Randomised and quasi-randomised controlled trials that compared (1) NSOMT versus placebo or control; and (2) NSOMT as adjunctive treatment or speech intervention versus speech intervention alone, for children aged three to 16 years with developmental speech sound disorders, as judged by a speech and language therapist. Individuals with an intellectual disability (e.g. Down syndrome) or a physical disability were not excluded. The Trials Search Co-ordinator of the Cochrane Developmental, Psychosocial and
ERIC Educational Resources Information Center
Lee, Jimin; Hustad, Katherine C.; Weismer, Gary
2014-01-01
Purpose: Speech acoustic characteristics of children with cerebral palsy (CP) were examined with a multiple speech subsystems approach; speech intelligibility was evaluated using a prediction model in which acoustic measures were selected to represent three speech subsystems. Method: Nine acoustic variables reflecting different subsystems, and…
Assessing Disfluencies in School-Age Children Who Stutter: How Much Speech Is Enough?
ERIC Educational Resources Information Center
Gregg, Brent A.; Sawyer, Jean
2015-01-01
The question of what size speech sample is sufficient to accurately identify stuttering and its myriad characteristics is a valid one. Short samples have a risk of over- or underrepresenting disfluency types or characteristics. In recent years, there has been a trend toward using shorter samples because they are less time-consuming for…
Lee, Jimin; Hustad, Katherine C; Weismer, Gary
2014-10-01
Speech acoustic characteristics of children with cerebral palsy (CP) were examined with a multiple speech subsystems approach; speech intelligibility was evaluated using a prediction model in which acoustic measures were selected to represent three speech subsystems. Nine acoustic variables reflecting different subsystems, and speech intelligibility, were measured in 22 children with CP. These children included 13 with a clinical diagnosis of dysarthria (speech motor impairment [SMI] group) and 9 judged to be free of dysarthria (no SMI [NSMI] group). Data from children with CP were compared to data from age-matched typically developing children. Multiple acoustic variables reflecting the articulatory subsystem were different in the SMI group, compared to the NSMI and typically developing groups. A significant speech intelligibility prediction model was obtained with all variables entered into the model (adjusted R2 = .801). The articulatory subsystem showed the most substantial independent contribution (58%) to speech intelligibility. Incremental R2 analyses revealed that any single variable explained less than 9% of speech intelligibility variability. Children in the SMI group had articulatory subsystem problems as indexed by acoustic measures. As in the adult literature, the articulatory subsystem makes the primary contribution to speech intelligibility variance in dysarthria, with minimal or no contribution from other systems.
Stasenko, Alena; Bonn, Cory; Teghipco, Alex; Garcea, Frank E; Sweet, Catherine; Dombovy, Mary; McDonough, Joyce; Mahon, Bradford Z
2015-01-01
The debate about the causal role of the motor system in speech perception has been reignited by demonstrations that motor processes are engaged during the processing of speech sounds. Here, we evaluate which aspects of auditory speech processing are affected, and which are not, in a stroke patient with dysfunction of the speech motor system. We found that the patient showed a normal phonemic categorical boundary when discriminating two non-words that differ by a minimal pair (e.g., ADA-AGA). However, using the same stimuli, the patient was unable to identify or label the non-word stimuli (using a button-press response). A control task showed that he could identify speech sounds by speaker gender, ruling out a general labelling impairment. These data suggest that while the motor system is not causally involved in perception of the speech signal, it may be used when other cues (e.g., meaning, context) are not available.
Li, X; Yang, Y; Ren, G
2009-06-16
Language is often perceived together with visual information. Recent experimental evidences indicated that, during spoken language comprehension, the brain can immediately integrate visual information with semantic or syntactic information from speech. Here we used the mismatch negativity to further investigate whether prosodic information from speech could be immediately integrated into a visual scene context or not, and especially the time course and automaticity of this integration process. Sixteen Chinese native speakers participated in the study. The materials included Chinese spoken sentences and picture pairs. In the audiovisual situation, relative to the concomitant pictures, the spoken sentence was appropriately accented in the standard stimuli, but inappropriately accented in the two kinds of deviant stimuli. In the purely auditory situation, the speech sentences were presented without pictures. It was found that the deviants evoked mismatch responses in both audiovisual and purely auditory situations; the mismatch negativity in the purely auditory situation peaked at the same time as, but was weaker than that evoked by the same deviant speech sounds in the audiovisual situation. This pattern of results suggested immediate integration of prosodic information from speech and visual information from pictures in the absence of focused attention.
The Relationship between Speech Production and Speech Perception Deficits in Parkinson's Disease
ERIC Educational Resources Information Center
De Keyser, Kim; Santens, Patrick; Bockstael, Annelies; Botteldooren, Dick; Talsma, Durk; De Vos, Stefanie; Van Cauwenberghe, Mieke; Verheugen, Femke; Corthals, Paul; De Letter, Miet
2016-01-01
Purpose: This study investigated the possible relationship between hypokinetic speech production and speech intensity perception in patients with Parkinson's disease (PD). Method: Participants included 14 patients with idiopathic PD and 14 matched healthy controls (HCs) with normal hearing and cognition. First, speech production was objectified…
Chaspari, Theodora; Soldatos, Constantin; Maragos, Petros
2015-01-01
The development of ecologically valid procedures for collecting reliable and unbiased emotional data towards computer interfaces with social and affective intelligence targeting patients with mental disorders. Following its development, presented with, the Athens Emotional States Inventory (AESI) proposes the design, recording and validation of an audiovisual database for five emotional states: anger, fear, joy, sadness and neutral. The items of the AESI consist of sentences each having content indicative of the corresponding emotion. Emotional content was assessed through a survey of 40 young participants with a questionnaire following the Latin square design. The emotional sentences that were correctly identified by 85% of the participants were recorded in a soundproof room with microphones and cameras. A preliminary validation of AESI is performed through automatic emotion recognition experiments from speech. The resulting database contains 696 recorded utterances in Greek language by 20 native speakers and has a total duration of approximately 28 min. Speech classification results yield accuracy up to 75.15% for automatically recognizing the emotions in AESI. These results indicate the usefulness of our approach for collecting emotional data with reliable content, balanced across classes and with reduced environmental variability.
Visual speech information: a help or hindrance in perceptual processing of dysarthric speech.
Borrie, Stephanie A
2015-03-01
This study investigated the influence of visual speech information on perceptual processing of neurologically degraded speech. Fifty listeners identified spastic dysarthric speech under both audio (A) and audiovisual (AV) conditions. Condition comparisons revealed that the addition of visual speech information enhanced processing of the neurologically degraded input in terms of (a) acuity (percent phonemes correct) of vowels and consonants and (b) recognition (percent words correct) of predictive and nonpredictive phrases. Listeners exploited stress-based segmentation strategies more readily in AV conditions, suggesting that the perceptual benefit associated with adding visual speech information to the auditory signal-the AV advantage-has both segmental and suprasegmental origins. Results also revealed that the magnitude of the AV advantage can be predicted, to some degree, by the extent to which an individual utilizes syllabic stress cues to inform word recognition in AV conditions. Findings inform the development of a listener-specific model of speech perception that applies to processing of dysarthric speech in everyday communication contexts.
Knowles, J C; Chalian, V A; Shanks, J C
1984-02-01
Surgery for cancer of the floor of the mouth often results in alteration of the muscles of the tongue and floor of the mouth. Both primary and secondary surgical procedures often result in scar formation with reduced mobility of the tongue during speech and deglutition. Speech is often used as a diagnostic tool in the placement of the anterior teeth during fabrication of a prosthesis. Speech can similarly be used to help determine the proper placement of a speech portion of the prosthesis. The prosthetic rehabilitation approach described lowers the palatal vault with a false palate to enable the tongue to function against it during speech (Fig. 15). Group studies have shown that the design and fabrication of speech prostheses for partial glossectomy patients have significantly improved speech and swallowing for these patients. A speech pathologist is helpful during diagnosis, and speech therapy is necessary for significant speech improvement. Prosthetic rehabilitation alone cannot be expected to improve 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.
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
ERIC Educational Resources Information Center
Boets, Bart; Wouters, Jan; van Wieringen, Astrid; De Smedt, Bert; Ghesquiere, Pol
2008-01-01
The general magnocellular theory postulates that dyslexia is the consequence of a multimodal deficit in the processing of transient and dynamic stimuli. In the auditory modality, this deficit has been hypothesized to interfere with accurate speech perception, and subsequently disrupt the development of phonological and later reading and spelling…
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…
Automatic Astrometric and Photometric Calibration with SCAMP
NASA Astrophysics Data System (ADS)
Bertin, E.
2006-07-01
Astrometric and photometric calibrations have remained the most tiresome step in the reduction of large imaging surveys. I present a new software package, SCAMP which has been written to address this problem. SCAMP efficiently computes accurate astrometric and photometric solutions for any arbitrary sequence of FITS images in a completely automatic way. SCAMP is released under the GNU General Public Licence.