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.
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.
Using Speech Recognition Software
Author: Calais J. Ingel
Publisher:
ISBN: 9780615525501
Category : Business & Economics
Languages : en
Pages : 310
Book Description
Ingel presents two variations of the speech recognition software--the "hands-free" method using speech only, and the "combination method," leveraging the advantages of both speech recognition techniques and traditional manual techniques.
Publisher:
ISBN: 9780615525501
Category : Business & Economics
Languages : en
Pages : 310
Book Description
Ingel presents two variations of the speech recognition software--the "hands-free" method using speech only, and the "combination method," leveraging the advantages of both speech recognition techniques and traditional manual techniques.
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.
Speech Recognition Using Articulatory and Excitation Source Features
Author: K. Sreenivasa Rao
Publisher: Springer
ISBN: 3319492209
Category : Technology & Engineering
Languages : en
Pages : 100
Book Description
This book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performance. Speech recognition is analyzed for read, extempore, and conversation modes of speech. Five groups of articulatory features (AFs) are explored for speech recognition, in addition to conventional spectral features. Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features. The authors close by discussing various combinations of spectral, articulatory and source features, and the desired models to enhance the performance of SR systems.
Publisher: Springer
ISBN: 3319492209
Category : Technology & Engineering
Languages : en
Pages : 100
Book Description
This book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performance. Speech recognition is analyzed for read, extempore, and conversation modes of speech. Five groups of articulatory features (AFs) are explored for speech recognition, in addition to conventional spectral features. Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features. The authors close by discussing various combinations of spectral, articulatory and source features, and the desired models to enhance the performance of SR systems.
The Writer's Guide to Training Your Dragon
Author: Scott Baker
Publisher: Ashe Publishing
ISBN:
Category : Language Arts & Disciplines
Languages : en
Pages : 83
Book Description
Want to dictate up to 5000 WORDS an hour? Want to do it with 99% ACCURACY from the day you start? NEW EDITION: UPDATED to cover the latest Dragon Professional Individual v15 for PC & v6 for Mac FREE video training included! As writers, we all know what an incredible tool dictation software can be. It enables us to write faster and avoid the dangers of RSI and a sedentary lifestyle. But many of us give up on dictating when we find we can't get the accuracy we need to be truly productive. This book changes all of that. With almost two decades of using Dragon software under his belt and a wealth of insider knowledge from within the dictation industry, Scott Baker will reveal how to supercharge your writing and achieve sky-high recognition accuracy from the moment you start using the software. You will learn: - Hidden tricks to use when installing Dragon NaturallySpeaking on a Windows PC or Dragon Dictate for Mac; - How to choose the right microphone and set it up perfectly for speech recognition; - The little-known techniques that will ensure around 99% accuracy from your first install – and how to make this even better over time; - Setting up fail-safe dictation profiles with multiple microphones and voice recorders, without impacting your accuracy; - How to train the software to adapt to both your voice AND writing style and avoid your accuracy declining; - Strategies for achieving your entire daily word count in just one or two hours; - Many more tips and tricks you won't find anywhere else. At the end of the book, you'll also find an exclusive list of resources and links to FREE video training to take your knowledge even further. It's time to write at the speed of speech – and transform your writing workflow forever! Subject keywords: Dragon Dictate Naturally Speaking for PC Mac, dictating your book or novel, dictation for writers authors beginners advanced, creative writing guides, self publishing
Publisher: Ashe Publishing
ISBN:
Category : Language Arts & Disciplines
Languages : en
Pages : 83
Book Description
Want to dictate up to 5000 WORDS an hour? Want to do it with 99% ACCURACY from the day you start? NEW EDITION: UPDATED to cover the latest Dragon Professional Individual v15 for PC & v6 for Mac FREE video training included! As writers, we all know what an incredible tool dictation software can be. It enables us to write faster and avoid the dangers of RSI and a sedentary lifestyle. But many of us give up on dictating when we find we can't get the accuracy we need to be truly productive. This book changes all of that. With almost two decades of using Dragon software under his belt and a wealth of insider knowledge from within the dictation industry, Scott Baker will reveal how to supercharge your writing and achieve sky-high recognition accuracy from the moment you start using the software. You will learn: - Hidden tricks to use when installing Dragon NaturallySpeaking on a Windows PC or Dragon Dictate for Mac; - How to choose the right microphone and set it up perfectly for speech recognition; - The little-known techniques that will ensure around 99% accuracy from your first install – and how to make this even better over time; - Setting up fail-safe dictation profiles with multiple microphones and voice recorders, without impacting your accuracy; - How to train the software to adapt to both your voice AND writing style and avoid your accuracy declining; - Strategies for achieving your entire daily word count in just one or two hours; - Many more tips and tricks you won't find anywhere else. At the end of the book, you'll also find an exclusive list of resources and links to FREE video training to take your knowledge even further. It's time to write at the speed of speech – and transform your writing workflow forever! Subject keywords: Dragon Dictate Naturally Speaking for PC Mac, dictating your book or novel, dictation for writers authors beginners advanced, creative writing guides, self publishing
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
Connectionist Speech Recognition
Author: Hervé A. Bourlard
Publisher: Springer Science & Business Media
ISBN: 1461532108
Category : Technology & Engineering
Languages : en
Pages : 329
Book Description
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.
Publisher: Springer Science & Business Media
ISBN: 1461532108
Category : Technology & Engineering
Languages : en
Pages : 329
Book Description
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.
Robust Speech Recognition of Uncertain or Missing Data
Author: Dorothea Kolossa
Publisher: Springer Science & Business Media
ISBN: 3642213170
Category : Technology & Engineering
Languages : en
Pages : 387
Book Description
Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition. The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models.
Publisher: Springer Science & Business Media
ISBN: 3642213170
Category : Technology & Engineering
Languages : en
Pages : 387
Book Description
Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition. The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models.
Automatic Speech and Speaker Recognition
Author: Chin-Hui Lee
Publisher: Springer Science & Business Media
ISBN: 1461313678
Category : Technology & Engineering
Languages : en
Pages : 524
Book Description
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.
Publisher: Springer Science & Business Media
ISBN: 1461313678
Category : Technology & Engineering
Languages : en
Pages : 524
Book Description
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.
Technology and Assessment
Author: National Research Council
Publisher: National Academies Press
ISBN: 0309083206
Category : Technology & Engineering
Languages : en
Pages : 208
Book Description
The papers in this collection were commissioned by the Board on Testing and Assessment (BOTA) of the National Research Council (NRC) for a workshop held on November 14, 2001, with support from the William and Flora Hewlett Foundation. Goals for the workshop were twofold. One was to share the major messages of the recently released NRC committee report, Knowing What Students Know: The Science and Design of Educational Assessment (2001), which synthesizes advances in the cognitive sciences and methods of measurement, and considers their implications for improving educational assessment. The second goal was to delve more deeply into one of the major themes of that report-the role that technology could play in bringing those advances together, which is the focus of these papers. For the workshop, selected researchers working in the intersection of technology and assessment were asked to write about some of the challenges and opportunities for more fully capitalizing on the power of information technologies to improve assessment, to illustrate those issues with examples from their own research, and to identify priorities for research and development in this area.
Publisher: National Academies Press
ISBN: 0309083206
Category : Technology & Engineering
Languages : en
Pages : 208
Book Description
The papers in this collection were commissioned by the Board on Testing and Assessment (BOTA) of the National Research Council (NRC) for a workshop held on November 14, 2001, with support from the William and Flora Hewlett Foundation. Goals for the workshop were twofold. One was to share the major messages of the recently released NRC committee report, Knowing What Students Know: The Science and Design of Educational Assessment (2001), which synthesizes advances in the cognitive sciences and methods of measurement, and considers their implications for improving educational assessment. The second goal was to delve more deeply into one of the major themes of that report-the role that technology could play in bringing those advances together, which is the focus of these papers. For the workshop, selected researchers working in the intersection of technology and assessment were asked to write about some of the challenges and opportunities for more fully capitalizing on the power of information technologies to improve assessment, to illustrate those issues with examples from their own research, and to identify priorities for research and development in this area.