Author: Richard L. Klevans
Publisher: Artech House Telecommunication
ISBN:
Category : Computers
Languages : en
Pages : 202
Book Description
Here's a scientific look at computer-generated speech verification and identification -- its underlying technology, practical applications, and future direction. You get a solid background in voice recognition technology to help you make informed decisions on which voice recognition-based software to use in your company or organization. It is unique in its clear explanations of mathematical concepts, as well as its full-chapter presentation of the successful new Multi-Granular Segregating System for accurate, context-free speech identification.
Voice Recognition
Author: Richard L. Klevans
Publisher: Artech House Telecommunication
ISBN:
Category : Computers
Languages : en
Pages : 202
Book Description
Here's a scientific look at computer-generated speech verification and identification -- its underlying technology, practical applications, and future direction. You get a solid background in voice recognition technology to help you make informed decisions on which voice recognition-based software to use in your company or organization. It is unique in its clear explanations of mathematical concepts, as well as its full-chapter presentation of the successful new Multi-Granular Segregating System for accurate, context-free speech identification.
Publisher: Artech House Telecommunication
ISBN:
Category : Computers
Languages : en
Pages : 202
Book Description
Here's a scientific look at computer-generated speech verification and identification -- its underlying technology, practical applications, and future direction. You get a solid background in voice recognition technology to help you make informed decisions on which voice recognition-based software to use in your company or organization. It is unique in its clear explanations of mathematical concepts, as well as its full-chapter presentation of the successful new Multi-Granular Segregating System for accurate, context-free speech identification.
Fundamentals of Speech Recognition
Author: Lawrence R. Rabiner
Publisher:
ISBN: 9788129701381
Category : Automatic speech recognition
Languages : en
Pages : 507
Book Description
Publisher:
ISBN: 9788129701381
Category : Automatic speech recognition
Languages : en
Pages : 507
Book Description
Readings in Speech Recognition
Author: Alexander Waibel
Publisher: Elsevier
ISBN: 0080515843
Category : Computers
Languages : en
Pages : 640
Book Description
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.
Publisher: Elsevier
ISBN: 0080515843
Category : Computers
Languages : en
Pages : 640
Book Description
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.
How to Build a Speech Recognition Application
Author: Bruce Balentine
Publisher:
ISBN: 9780967127811
Category : Automatic speech recognition
Languages : en
Pages : 0
Book Description
Publisher:
ISBN: 9780967127811
Category : Automatic speech recognition
Languages : en
Pages : 0
Book Description
Automatic Speech Recognition
Author: Dong Yu
Publisher: Springer
ISBN: 1447157796
Category : Technology & Engineering
Languages : en
Pages : 329
Book Description
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.
Publisher: Springer
ISBN: 1447157796
Category : Technology & Engineering
Languages : en
Pages : 329
Book Description
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.
Voice Recognition by Computer
Author: Milan Sigmund
Publisher: Tectum Verlag DE
ISBN: 9783828884922
Category :
Languages : en
Pages : 114
Book Description
Publisher: Tectum Verlag DE
ISBN: 9783828884922
Category :
Languages : en
Pages : 114
Book Description
Statistical Methods for Speech Recognition
Author: Frederick Jelinek
Publisher: MIT Press
ISBN: 0262546604
Category : Language Arts & Disciplines
Languages : en
Pages : 307
Book Description
This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques. Bradford Books imprint
Publisher: MIT Press
ISBN: 0262546604
Category : Language Arts & Disciplines
Languages : en
Pages : 307
Book Description
This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques. Bradford Books imprint
Deep Learning for NLP and Speech Recognition
Author: Uday Kamath
Publisher: Springer
ISBN: 3030145964
Category : Computers
Languages : en
Pages : 640
Book Description
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.
Publisher: Springer
ISBN: 3030145964
Category : Computers
Languages : en
Pages : 640
Book Description
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
Author: France Mihelič
Publisher: BoD – Books on Demand
ISBN: 953761929X
Category : Computers
Languages : en
Pages : 580
Book Description
Chapters in the first part of the book cover all the essential speech processing techniques for building robust, automatic speech recognition systems: the representation for speech signals and the methods for speech-features extraction, acoustic and language modeling, efficient algorithms for searching the hypothesis space, and multimodal approaches to speech recognition. The last part of the book is devoted to other speech processing applications that can use the information from automatic speech recognition for speaker identification and tracking, for prosody modeling in emotion-detection systems and in other speech processing applications that are able to operate in real-world environments, like mobile communication services and smart homes.
Publisher: BoD – Books on Demand
ISBN: 953761929X
Category : Computers
Languages : en
Pages : 580
Book Description
Chapters in the first part of the book cover all the essential speech processing techniques for building robust, automatic speech recognition systems: the representation for speech signals and the methods for speech-features extraction, acoustic and language modeling, efficient algorithms for searching the hypothesis space, and multimodal approaches to speech recognition. The last part of the book is devoted to other speech processing applications that can use the information from automatic speech recognition for speaker identification and tracking, for prosody modeling in emotion-detection systems and in other speech processing applications that are able to operate in real-world environments, like mobile communication services and smart homes.
SPEECH RECOGNITION: THEORY AND C++ IMPLEMENTATION (With CD )
Author: Claudio Becchetti
Publisher: John Wiley & Sons
ISBN: 9788126517749
Category :
Languages : en
Pages : 432
Book Description
Special Features: · Source codes for compiling and implementing ASR algorithms in C++ are included in electronic format on an accompanying CD-ROM· Contains a practical account of the functioning of ASR· Includes implementation-oriented mathematical and technical explanations of ASR· Features a stage-by-stage explanation of how to create an ASR interface· Can be used both for teaching speech recognition techniques and testing and development of new systems on digital signal processing hardware About The Book: Automatic Speech Recognition (ASR) is becoming increasingly prevalent in such applications as private telephone exchanges and real-time on-line telephone information services. This book introduces the principles of ASR systems, including the theory and the implementation issues behind multi-speaker continuous speech ASR. The book supplies the full C++ code to further clarify the implementation details of a typical commercial/laboratory ASR system and to allow the readers to reach practical solutions for ASR-related problems.About the topic/technology Automatic Speech Recognition (ASR) is the technology behind the voice-triggered computer menus. Uses of these systems are now proliferating rapidly and include private telephone exchanges and real-time on-line telephone information services.
Publisher: John Wiley & Sons
ISBN: 9788126517749
Category :
Languages : en
Pages : 432
Book Description
Special Features: · Source codes for compiling and implementing ASR algorithms in C++ are included in electronic format on an accompanying CD-ROM· Contains a practical account of the functioning of ASR· Includes implementation-oriented mathematical and technical explanations of ASR· Features a stage-by-stage explanation of how to create an ASR interface· Can be used both for teaching speech recognition techniques and testing and development of new systems on digital signal processing hardware About The Book: Automatic Speech Recognition (ASR) is becoming increasingly prevalent in such applications as private telephone exchanges and real-time on-line telephone information services. This book introduces the principles of ASR systems, including the theory and the implementation issues behind multi-speaker continuous speech ASR. The book supplies the full C++ code to further clarify the implementation details of a typical commercial/laboratory ASR system and to allow the readers to reach practical solutions for ASR-related problems.About the topic/technology Automatic Speech Recognition (ASR) is the technology behind the voice-triggered computer menus. Uses of these systems are now proliferating rapidly and include private telephone exchanges and real-time on-line telephone information services.