Speech Recognition By Machine
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Robust Automatic Speech Recognition
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Author : Jinyu Li
language : en
Publisher: Academic Press
Release Date : 2015-10-30
Robust Automatic Speech Recognition written by Jinyu Li and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-30 with Technology & Engineering categories.
Robust Automatic Speech Recognition: A Bridge to Practical Applications establishes a solid foundation for automatic speech recognition that is robust against acoustic environmental distortion. It provides a thorough overview of classical and modern noise-and reverberation robust techniques that have been developed over the past thirty years, with an emphasis on practical methods that have been proven to be successful and which are likely to be further developed for future applications.The strengths and weaknesses of robustness-enhancing speech recognition techniques are carefully analyzed. The book covers noise-robust techniques designed for acoustic models which are based on both Gaussian mixture models and deep neural networks. In addition, a guide to selecting the best methods for practical applications is provided.The reader will: - Gain a unified, deep and systematic understanding of the state-of-the-art technologies for robust speech recognition - Learn the links and relationship between alternative technologies for robust speech recognition - Be able to use the technology analysis and categorization detailed in the book to guide future technology development - Be able to develop new noise-robust methods in the current era of deep learning for acoustic modeling in speech recognition - The first book that provides a comprehensive review on noise and reverberation robust speech recognition methods in the era of deep neural networks - Connects robust speech recognition techniques to machine learning paradigms with rigorous mathematical treatment - Provides elegant and structural ways to categorize and analyze noise-robust speech recognition techniques - Written by leading researchers who have been actively working on the subject matter in both industrial and academic organizations for many years
Speech Recognition By Machine
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Author : William Anthony Ainsworth
language : en
Publisher: INSPEC, Incorporated
Release Date : 1988
Speech Recognition By Machine written by William Anthony Ainsworth and has been published by INSPEC, Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Computers categories.
The Recognition Of Speech By Machine
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Author : Arthur S. House
language : en
Publisher:
Release Date : 1988
The Recognition Of Speech By Machine written by Arthur S. House and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Computers categories.
This bibliography aims to provide an easily accessible and thus convenient reference source for all those with an interest in automatic speech recognition and speech technology. The coverage is extensive and up-to-date and provides a historical perspective, as well as a reference point for recent work. Whether it is used merely to check references or as a starting point for an exploration of this field of research, this volume will prove an invaluable addition to any personal or institutional library.
Voice Communication Between Humans And Machines
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Author : for the National Academy of Sciences
language : en
Publisher: National Academies Press
Release Date : 1994-02-01
Voice Communication Between Humans And Machines written by for the National Academy of Sciences and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-02-01 with Technology & Engineering categories.
Science fiction has long been populated with conversational computers and robots. Now, speech synthesis and recognition have matured to where a wide range of real-world applicationsâ€"from serving people with disabilities to boosting the nation's competitivenessâ€"are within our grasp. Voice Communication Between Humans and Machines takes the first interdisciplinary look at what we know about voice processing, where our technologies stand, and what the future may hold for this fascinating field. The volume integrates theoretical, technical, and practical views from world-class experts at leading research centers around the world, reporting on the scientific bases behind human-machine voice communication, the state of the art in computerization, and progress in user friendliness. It offers an up-to-date treatment of technological progress in key areas: speech synthesis, speech recognition, and natural language understanding. The book also explores the emergence of the voice processing industry and specific opportunities in telecommunications and other businesses, in military and government operations, and in assistance for the disabled. It outlines, as well, practical issues and research questions that must be resolved if machines are to become fellow problem-solvers along with humans. Voice Communication Between Humans and Machines provides a comprehensive understanding of the field of voice processing for engineers, researchers, and business executives, as well as speech and hearing specialists, advocates for people with disabilities, faculty and students, and interested individuals.
Automatic Speech And Speaker Recognition
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Author : Joseph Keshet
language : en
Publisher: John Wiley & Sons
Release Date : 2009-04-27
Automatic Speech And Speaker Recognition written by Joseph Keshet and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-04-27 with Technology & Engineering categories.
This book discusses large margin and kernel methods for speech and speaker recognition Speech and Speaker Recognition: Large Margin and Kernel Methods is a collation of research in the recent advances in large margin and kernel methods, as applied to the field of speech and speaker recognition. It presents theoretical and practical foundations of these methods, from support vector machines to large margin methods for structured learning. It also provides examples of large margin based acoustic modelling for continuous speech recognizers, where the grounds for practical large margin sequence learning are set. Large margin methods for discriminative language modelling and text independent speaker verification are also addressed in this book. Key Features: Provides an up-to-date snapshot of the current state of research in this field Covers important aspects of extending the binary support vector machine to speech and speaker recognition applications Discusses large margin and kernel method algorithms for sequence prediction required for acoustic modeling Reviews past and present work on discriminative training of language models, and describes different large margin algorithms for the application of part-of-speech tagging Surveys recent work on the use of kernel approaches to text-independent speaker verification, and introduces the main concepts and algorithms Surveys recent work on kernel approaches to learning a similarity matrix from data This book will be of interest to researchers, practitioners, engineers, and scientists in speech processing and machine learning fields.
The Voice In The Machine
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Author : Roberto Pieraccini
language : en
Publisher: MIT Press
Release Date : 2012
The Voice In The Machine written by Roberto Pieraccini and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.
An examination of more than sixty years of successes and failures in developing technologies that allow computers to understand human spoken language. Stanley Kubrick's 1968 film 2001: A Space Odyssey famously featured HAL, a computer with the ability to hold lengthy conversations with his fellow space travelers. More than forty years later, we have advanced computer technology that Kubrick never imagined, but we do not have computers that talk and understand speech as HAL did. Is it a failure of our technology that we have not gotten much further than an automated voice that tells us to "say or press 1"? Or is there something fundamental in human language and speech that we do not yet understand deeply enough to be able to replicate in a computer? In The Voice in the Machine, Roberto Pieraccini examines six decades of work in science and technology to develop computers that can interact with humans using speech and the industry that has arisen around the quest for these technologies. He shows that although the computers today that understand speech may not have HAL's capacity for conversation, they have capabilities that make them usable in many applications today and are on a fast track of improvement and innovation. Pieraccini describes the evolution of speech recognition and speech understanding processes from waveform methods to artificial intelligence approaches to statistical learning and modeling of human speech based on a rigorous mathematical model--specifically, Hidden Markov Models (HMM). He details the development of dialog systems, the ability to produce speech, and the process of bringing talking machines to the market. Finally, he asks a question that only the future can answer: will we end up with HAL-like computers or something completely unexpected?
Deep Learning For Nlp And Speech Recognition
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Author : Uday Kamath
language : en
Publisher: Springer
Release Date : 2019-06-10
Deep Learning For Nlp And Speech Recognition written by Uday Kamath and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-10 with Computers categories.
This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.
Speech Recognition By Machine Microform
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Author : Bryden, Brian Richard
language : en
Publisher: National Library of Canada
Release Date : 1970
Speech Recognition By Machine Microform written by Bryden, Brian Richard and has been published by National Library of Canada this book supported file pdf, txt, epub, kindle and other format this book has been release on 1970 with categories.
Privacy Preserving Machine Learning For Speech Processing
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Author : Manas A. Pathak
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-10-25
Privacy Preserving Machine Learning For Speech Processing written by Manas A. Pathak and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-25 with Computers categories.
"Doctoral Thesis accepted by Carnegie Mellon University, USA"--Title page.
Speech Recognition By Man And Machine
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Author : Bernd T. Meyer
language : en
Publisher: Sudwestdeutscher Verlag Fur Hochschulschriften AG
Release Date : 2010-11
Speech Recognition By Man And Machine written by Bernd T. Meyer and has been published by Sudwestdeutscher Verlag Fur Hochschulschriften AG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11 with categories.
While human listeners have little problems in dealing with the strong variation in spoken language, the same cannot be said about automatic speech recognition (ASR). This work compares recognition performance of man and machine with the aim of learning from the distinct errors between these two. Based on the differences, the signal processing mechanisms are analyzed that are suitable to increase the robustness of ASR. The comparison focuses on the influence of intrinsic variation of speech, i.e., changes in speaking rate, effort and style, as well as dialect and accent. The outcome of the experiments suggests that the processing of temporal cues in ASR bears room for improvement. Therefore, spectro-temporal features are employed as input to ASR systems, which results in an increase of recognition performance for varying speaking effort and speaking style compared to standard features. This documents the usefulness of spectro-temporal and temporal information for automatic recognizers.