The listening talker: A review of human and algorithmic context-induced modifications of speech

International audienceSpeech output technology is finding widespread application, including in scenarios where intelligibility might be compromised - at least for some listeners - by adverse conditions. Unlike most current algorithms, talkers continually adapt their speech patterns as a response to the immediate context of spoken communication, where the type of interlocutor and the environment are the dominant situational factors influencing speech production. Observations of talker behaviour can motivate the design of more robust speech output algorithms. Starting with a listener-oriented categorisation of possible goals for speech modification, this review article summarises the extensive set of behavioural findings related to human speech modification, identifies which factors appear to be beneficial, and goes on to examine previous computational attempts to improve intelligibility in noise. The review concludes by tabulating 46 speech modifications, many of which have yet to be perceptually or algorithmically evaluated. Consequently, the review provides a roadmap for future work in improving the robustness of speech output

Visual Speech Recognition using Histogram of Oriented Displacements

Lip reading is the recognition of spoken words from the visual information of lips. It has been of considerable interest in the Computer Vision and Speech Recognition communities to automate this process using computer algorithms. In this thesis, we have developed a novel method involving describing visual features using fixed length descriptors called Histogram of Oriented Displacements to which we apply Support Vector Machines for recognition of spoken words. Using this method on the CUAVE database we have achieved a recognition rate of 81%

The Unsupervised Acquisition of a Lexicon from Continuous Speech

We present an unsupervised learning algorithm that acquires a natural-language lexicon from raw speech. The algorithm is based on the optimal encoding of symbol sequences in an MDL framework, and uses a hierarchical representation of language that overcomes many of the problems that have stymied previous grammar-induction procedures. The forward mapping from symbol sequences to the speech stream is modeled using features based on articulatory gestures. We present results on the acquisition of lexicons and language models from raw speech, text, and phonetic transcripts, and demonstrate that our algorithm compares very favorably to other reported results with respect to segmentation performance and statistical efficiency.Comment: 27 page technical repor

A Silent-Speech Interface using Electro-Optical Stomatography

Sprachtechnologie ist eine große und wachsende Industrie, die das Leben von technologieinteressierten Nutzern auf zahlreichen Wegen bereichert. Viele potenzielle Nutzer werden jedoch ausgeschlossen: Nämlich alle Sprecher, die nur schwer oder sogar gar nicht Sprache produzieren können. Silent-Speech Interfaces bieten einen Weg, mit Maschinen durch ein bequemes sprachgesteuertes Interface zu kommunizieren ohne dafür akustische Sprache zu benötigen. Sie können außerdem prinzipiell eine Ersatzstimme stellen, indem sie die intendierten Äußerungen, die der Nutzer nur still artikuliert, künstlich synthetisieren. Diese Dissertation stellt ein neues Silent-Speech Interface vor, das auf einem neu entwickelten Messsystem namens Elektro-Optischer Stomatografie und einem neuartigen parametrischen Vokaltraktmodell basiert, das die Echtzeitsynthese von Sprache basierend auf den gemessenen Daten ermöglicht. Mit der Hardware wurden Studien zur Einzelworterkennung durchgeführt, die den Stand der Technik in der intra- und inter-individuellen Genauigkeit erreichten und übertrafen. Darüber hinaus wurde eine Studie abgeschlossen, in der die Hardware zur Steuerung des Vokaltraktmodells in einer direkten Artikulation-zu-Sprache-Synthese verwendet wurde. Während die Verständlichkeit der Synthese von Vokalen sehr hoch eingeschätzt wurde, ist die Verständlichkeit von Konsonanten und kontinuierlicher Sprache sehr schlecht. Vielversprechende Möglichkeiten zur Verbesserung des Systems werden im Ausblick diskutiert.:Statement of authorship iii Abstract v List of Figures vii List of Tables xi Acronyms xiii 1. Introduction 1 1.1. The concept of a Silent-Speech Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2. Structure of this work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2. Fundamentals of phonetics 7 2.1. Components of the human speech production system . . . . . . . . . . . . . . . . . . . 7 2.2. Vowel sounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.3. Consonantal sounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.4. Acoustic properties of speech sounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.5. Coarticulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.6. Phonotactics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.7. Summary and implications for the design of a Silent-Speech Interface (SSI) . . . . . . . 21 3. Articulatory data acquisition techniques in Silent-Speech Interfaces 25 3.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.2. Scope of the literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.3. Video Recordings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.4. Ultrasonography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.5. Electromyography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.6. Permanent-Magnetic Articulography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 3.7. Electromagnetic Articulography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.8. Radio waves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 3.9. Palatography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 3.10.Conclusion and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 4. Electro-Optical Stomatography 55 4.1. Contact sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.2. Optical distance sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 4.3. Lip sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 4.4. Sensor Unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 4.5. Control Unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 4.6. Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 5. Articulation-to-Text 99 5.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 5.2. Command word recognition pilot study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 5.3. Command word recognition small-scale study . . . . . . . . . . . . . . . . . . . . . . . . 102 6. Articulation-to-Speech 109 6.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 6.2. Articulatory synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 6.3. The six point vocal tract model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 6.4. Objective evaluation of the vocal tract model . . . . . . . . . . . . . . . . . . . . . . . . 116 6.5. Perceptual evaluation of the vocal tract model . . . . . . . . . . . . . . . . . . . . . . . . 120 6.6. Direct synthesis using EOS to control the vocal tract model . . . . . . . . . . . . . . . . 125 6.7. Pitch and voicing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 7. Summary and outlook 145 7.1. Summary of the contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 7.2. Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 A. Overview of the International Phonetic Alphabet 151 B. Mathematical proofs and derivations 153 B.1. Combinatoric calculations illustrating the reduction of possible syllables using phonotactics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 B.2. Signal Averaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 B.3. Effect of the contact sensor area on the conductance . . . . . . . . . . . . . . . . . . . . 155 B.4. Calculation of the forward current for the OP280V diode . . . . . . . . . . . . . . . . . . 155 C. Schematics and layouts 157 C.1. Schematics of the control unit. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 C.2. Layout of the control unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 C.3. Bill of materials of the control unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 C.4. Schematics of the sensor unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 C.5. Layout of the sensor unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 C.6. Bill of materials of the sensor unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 D. Sensor unit assembly 169 E. Firmware flow and data protocol 177 F. Palate file format 181 G. Supplemental material regarding the vocal tract model 183 H. Articulation-to-Speech: Optimal hyperparameters 189 Bibliography 191Speech technology is a major and growing industry that enriches the lives of technologically-minded people in a number of ways. Many potential users are, however, excluded: Namely, all speakers who cannot easily or even at all produce speech. Silent-Speech Interfaces offer a way to communicate with a machine by a convenient speech recognition interface without the need for acoustic speech. They also can potentially provide a full replacement voice by synthesizing the intended utterances that are only silently articulated by the user. To that end, the speech movements need to be captured and mapped to either text or acoustic speech. This dissertation proposes a new Silent-Speech Interface based on a newly developed measurement technology called Electro-Optical Stomatography and a novel parametric vocal tract model to facilitate real-time speech synthesis based on the measured data. The hardware was used to conduct command word recognition studies reaching state-of-the-art intra- and inter-individual performance. Furthermore, a study on using the hardware to control the vocal tract model in a direct articulation-to-speech synthesis loop was also completed. While the intelligibility of synthesized vowels was high, the intelligibility of consonants and connected speech was quite poor. Promising ways to improve the system are discussed in the outlook.:Statement of authorship iii Abstract v List of Figures vii List of Tables xi Acronyms xiii 1. Introduction 1 1.1. The concept of a Silent-Speech Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2. Structure of this work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2. Fundamentals of phonetics 7 2.1. Components of the human speech production system . . . . . . . . . . . . . . . . . . . 7 2.2. Vowel sounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.3. Consonantal sounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 2.4. Acoustic properties of speech sounds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 2.5. Coarticulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 2.6. Phonotactics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 2.7. Summary and implications for the design of a Silent-Speech Interface (SSI) . . . . . . . 21 3. Articulatory data acquisition techniques in Silent-Speech Interfaces 25 3.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 3.2. Scope of the literature review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.3. Video Recordings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 3.4. Ultrasonography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 3.5. Electromyography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.6. Permanent-Magnetic Articulography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 3.7. Electromagnetic Articulography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 3.8. Radio waves . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 3.9. Palatography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 3.10.Conclusion and Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 4. Electro-Optical Stomatography 55 4.1. Contact sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.2. Optical distance sensors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 4.3. Lip sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 4.4. Sensor Unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84 4.5. Control Unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 4.6. Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 5. Articulation-to-Text 99 5.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 5.2. Command word recognition pilot study . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 5.3. Command word recognition small-scale study . . . . . . . . . . . . . . . . . . . . . . . . 102 6. Articulation-to-Speech 109 6.1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 6.2. Articulatory synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 6.3. The six point vocal tract model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 113 6.4. Objective evaluation of the vocal tract model . . . . . . . . . . . . . . . . . . . . . . . . 116 6.5. Perceptual evaluation of the vocal tract model . . . . . . . . . . . . . . . . . . . . . . . . 120 6.6. Direct synthesis using EOS to control the vocal tract model . . . . . . . . . . . . . . . . 125 6.7. Pitch and voicing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 132 7. Summary and outlook 145 7.1. Summary of the contributions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 7.2. Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146 A. Overview of the International Phonetic Alphabet 151 B. Mathematical proofs and derivations 153 B.1. Combinatoric calculations illustrating the reduction of possible syllables using phonotactics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 B.2. Signal Averaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 B.3. Effect of the contact sensor area on the conductance . . . . . . . . . . . . . . . . . . . . 155 B.4. Calculation of the forward current for the OP280V diode . . . . . . . . . . . . . . . . . . 155 C. Schematics and layouts 157 C.1. Schematics of the control unit. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 C.2. Layout of the control unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 C.3. Bill of materials of the control unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 C.4. Schematics of the sensor unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 C.5. Layout of the sensor unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166 C.6. Bill of materials of the sensor unit . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167 D. Sensor unit assembly 169 E. Firmware flow and data protocol 177 F. Palate file format 181 G. Supplemental material regarding the vocal tract model 183 H. Articulation-to-Speech: Optimal hyperparameters 189 Bibliography 19

Sperry Univac speech communications technology

Technology and systems for effective verbal communication with computers were developed. A continuous speech recognition system for verbal input, a word spotting system to locate key words in conversational speech, prosodic tools to aid speech analysis, and a prerecorded voice response system for speech output are described

Mixed Distance Measures for Optimizing Concatenative Vocabularies for Speech Synthesis: A Thesis Proposal

Synthesized speech from text-to-speech systems is generally produced from the concatenation of small units of speech. The concatenation process can be complex, involving smoothing and context dependent adjustments to the speech. The overall quality of the speech produced will depend in large part on the quality of the elements used for concatenation. Selection and evaluation of these elements has been done entirely by hand. The proposed work addresses the process by which these concatenative elements are created from a natural voice and optimized. The optimization uses distance measures which exploit detailed information on the structure of the speech signals