Advancing Electromyographic Continuous Speech Recognition Signal Preprocessing And Modeling
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Author |
: Wand, Michael |
Publisher |
: KIT Scientific Publishing |
Total Pages |
: 256 |
Release |
: 2015-02-04 |
ISBN-10 |
: 9783731502111 |
ISBN-13 |
: 3731502119 |
Rating |
: 4/5 (11 Downloads) |
Synopsis Advancing Electromyographic Continuous Speech Recognition: Signal Preprocessing and Modeling by : Wand, Michael
Speech is the natural medium of human communication, but audible speech can be overheard by bystanders and excludes speech-disabled people. This work presents a speech recognizer based on surface electromyography, where electric potentials of the facial muscles are captured by surface electrodes, allowing speech to be processed nonacoustically. A system which was state-of-the-art at the beginning of this book is substantially improved in terms of accuracy, flexibility, and robustness.
Author |
: Michael Wand |
Publisher |
: |
Total Pages |
: 252 |
Release |
: 2020-10-09 |
ISBN-10 |
: 1013282574 |
ISBN-13 |
: 9781013282577 |
Rating |
: 4/5 (74 Downloads) |
Synopsis Advancing Electromyographic Continuous Speech Recognition by : Michael Wand
Speech is the natural medium of human communication, but audible speech can be overheard by bystanders and excludes speech-disabled people. This work presents a speech recognizer based on surface electromyography, where electric potentials of the facial muscles are captured by surface electrodes, allowing speech to be processed nonacoustically. A system which was state-of-the-art at the beginning of this book is substantially improved in terms of accuracy, flexibility, and robustness. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.
Author |
: Chin-Hui Lee |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 524 |
Release |
: 2012-12-06 |
ISBN-10 |
: 9781461313670 |
ISBN-13 |
: 1461313678 |
Rating |
: 4/5 (70 Downloads) |
Synopsis Automatic Speech and Speaker Recognition by : Chin-Hui Lee
Research in the field of automatic speech and speaker recognition has made a number of significant advances in the last two decades, influenced by advances in signal processing, algorithms, architectures, and hardware. These advances include: the adoption of a statistical pattern recognition paradigm; the use of the hidden Markov modeling framework to characterize both the spectral and the temporal variations in the speech signal; the use of a large set of speech utterance examples from a large population of speakers to train the hidden Markov models of some fundamental speech units; the organization of speech and language knowledge sources into a structural finite state network; and the use of dynamic, programming based heuristic search methods to find the best word sequence in the lexical network corresponding to the spoken utterance. Automatic Speech and Speaker Recognition: Advanced Topics groups together in a single volume a number of important topics on speech and speaker recognition, topics which are of fundamental importance, but not yet covered in detail in existing textbooks. Although no explicit partition is given, the book is divided into five parts: Chapters 1-2 are devoted to technology overviews; Chapters 3-12 discuss acoustic modeling of fundamental speech units and lexical modeling of words and pronunciations; Chapters 13-15 address the issues related to flexibility and robustness; Chapter 16-18 concern the theoretical and practical issues of search; Chapters 19-20 give two examples of algorithm and implementational aspects for recognition system realization. Audience: A reference book for speech researchers and graduate students interested in pursuing potential research on the topic. May also be used as a text for advanced courses on the subject.
Author |
: Wu Chou |
Publisher |
: CRC Press |
Total Pages |
: 413 |
Release |
: 2003-02-26 |
ISBN-10 |
: 9780203010525 |
ISBN-13 |
: 0203010523 |
Rating |
: 4/5 (25 Downloads) |
Synopsis Pattern Recognition in Speech and Language Processing by : Wu Chou
Over the last 20 years, approaches to designing speech and language processing algorithms have moved from methods based on linguistics and speech science to data-driven pattern recognition techniques. These techniques have been the focus of intense, fast-moving research and have contributed to significant advances in this field. Pattern Reco
Author |
: Sadaoki Furui |
Publisher |
: CRC Press |
Total Pages |
: 319 |
Release |
: 2018-05-04 |
ISBN-10 |
: 9781351990929 |
ISBN-13 |
: 1351990926 |
Rating |
: 4/5 (29 Downloads) |
Synopsis Digital Speech Processing by : Sadaoki Furui
A study of digital speech processing, synthesis and recognition. This second edition contains new sections on the international standardization of robust and flexible speech coding techniques, waveform unit concatenation-based speech synthesis, large vocabulary continuous-speech recognition based on statistical pattern recognition, and more.
Author |
: Nelson Morgan |
Publisher |
: |
Total Pages |
: 20 |
Release |
: 1995 |
ISBN-10 |
: OCLC:226451720 |
ISBN-13 |
: |
Rating |
: 4/5 (20 Downloads) |
Synopsis Speech Recognition by : Nelson Morgan
Author |
: Nilanjan Dey |
Publisher |
: Academic Press |
Total Pages |
: 212 |
Release |
: 2019-03-27 |
ISBN-10 |
: 9780128181317 |
ISBN-13 |
: 0128181311 |
Rating |
: 4/5 (17 Downloads) |
Synopsis Intelligent Speech Signal Processing by : Nilanjan Dey
Intelligent Speech Signal Processing investigates the utilization of speech analytics across several systems and real-world activities, including sharing data analytics, creating collaboration networks between several participants, and implementing video-conferencing in different application areas. Chapters focus on the latest applications of speech data analysis and management tools across different recording systems. The book emphasizes the multidisciplinary nature of the field, presenting different applications and challenges with extensive studies on the design, development and management of intelligent systems, neural networks and related machine learning techniques for speech signal processing. - Highlights different data analytics techniques in speech signal processing, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and neural networks techniques for speech signal processing - Includes coverage of biomodal speech recognition, voice activity detection, spoken language and speech disorder identification, automatic speech to speech summarization, and convolutional neural networks
Author |
: Dong Yu |
Publisher |
: Springer |
Total Pages |
: 329 |
Release |
: 2014-11-11 |
ISBN-10 |
: 9781447157793 |
ISBN-13 |
: 1447157796 |
Rating |
: 4/5 (93 Downloads) |
Synopsis Automatic Speech Recognition by : Dong Yu
This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.
Author |
: Hervé A. Bourlard |
Publisher |
: Springer Science & Business Media |
Total Pages |
: 329 |
Release |
: 2012-12-06 |
ISBN-10 |
: 9781461532101 |
ISBN-13 |
: 1461532108 |
Rating |
: 4/5 (01 Downloads) |
Synopsis Connectionist Speech Recognition by : Hervé A. Bourlard
Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction. The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems. Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods. Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing.
Author |
: Alexander Waibel |
Publisher |
: Elsevier |
Total Pages |
: 640 |
Release |
: 1990-12-25 |
ISBN-10 |
: 9780080515847 |
ISBN-13 |
: 0080515843 |
Rating |
: 4/5 (47 Downloads) |
Synopsis Readings in Speech Recognition by : Alexander Waibel
After more than two decades of research activity, speech recognition has begun to live up to its promise as a practical technology and interest in the field is growing dramatically. Readings in Speech Recognition provides a collection of seminal papers that have influenced or redirected the field and that illustrate the central insights that have emerged over the years. The editors provide an introduction to the field, its concerns and research problems. Subsequent chapters are devoted to the main schools of thought and design philosophies that have motivated different approaches to speech recognition system design. Each chapter includes an introduction to the papers that highlights the major insights or needs that have motivated an approach to a problem and describes the commonalities and differences of that approach to others in the book.