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Author : Jeff Bilmes
Publisher :
ISBN 13 :
Total Pages : 446 pages
Book Rating : 4.:/5 (32 download)
Download or read book Natural Statistical Models for Automatic Speech Recognition written by Jeff Bilmes and published by . This book was released on 1999 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Frederick Jelinek
Publisher : MIT Press
ISBN 13 : 0262546604
Total Pages : 307 pages
Book Rating : 4.2/5 (625 download)
Download or read book Statistical Methods for Speech Recognition written by Frederick Jelinek and published by MIT Press. This book was released on 2022-11-01 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Author : Keith Ponting
Publisher : Springer Science & Business Media
ISBN 13 : 3642600875
Total Pages : 478 pages
Book Rating : 4.6/5 (426 download)
Download or read book Computational Models of Speech Pattern Processing written by Keith Ponting and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the NATO Advanced Study Institute on Computational Models of Speech Pattern Processing, held in St. Helier, Jersey, UK, July 7-18, 1997
Author : Rainer E. Gruhn
Publisher : Springer Science & Business Media
ISBN 13 : 3642195865
Total Pages : 118 pages
Book Rating : 4.6/5 (421 download)
Download or read book Statistical Pronunciation Modeling for Non-Native Speech Processing written by Rainer E. Gruhn and published by Springer Science & Business Media. This book was released on 2011-05-08 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here. The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set of non-native English in the regarding accent. The book is written for researchers with a professional interest in phonetics and automatic speech and speaker recognition.
Author : Mark Gales
Publisher : Now Publishers Inc
ISBN 13 : 1601981201
Total Pages : 125 pages
Book Rating : 4.6/5 (19 download)
Download or read book The Application of Hidden Markov Models in Speech Recognition written by Mark Gales and published by Now Publishers Inc. This book was released on 2008 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.
Author : Carlos Martín-Vide
Publisher : Springer Nature
ISBN 13 : 3030313727
Total Pages : 326 pages
Book Rating : 4.0/5 (33 download)
Download or read book Statistical Language and Speech Processing written by Carlos Martín-Vide and published by Springer Nature. This book was released on 2019-09-27 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 7th International Conference on Statistical Language and Speech Processing, SLSP 2019, held in Ljubljana, Slovenia, in October 2019. The 25 full papers presented together with one invited paper in this volume were carefully reviewed and selected from 48 submissions. They were organized in topical sections named: Dialogue and Spoken Language Understanding; Language Analysis and Generation; Speech Analysis and Synthesis; Speech Recognition; Text Analysis and Classification.
Author : Sakriani Sakti
Publisher : Springer Science & Business Media
ISBN 13 : 038785830X
Total Pages : 207 pages
Book Rating : 4.3/5 (878 download)
Download or read book Incorporating Knowledge Sources into Statistical Speech Recognition written by Sakriani Sakti and published by Springer Science & Business Media. This book was released on 2009-02-27 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. The book provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systems. It can be applied to many existing ASR problems with their respective model-based likelihood functions in flexible ways.
Author : Dong Yu
Publisher : Springer
ISBN 13 : 1447157796
Total Pages : 329 pages
Book Rating : 4.4/5 (471 download)
Download or read book Automatic Speech Recognition written by Dong Yu and published by Springer. This book was released on 2014-11-11 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Mark Johnson
Publisher : Springer Science & Business Media
ISBN 13 : 1441990178
Total Pages : 292 pages
Book Rating : 4.4/5 (419 download)
Download or read book Mathematical Foundations of Speech and Language Processing written by Mark Johnson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Speech and language technologies continue to grow in importance as they are used to create natural and efficient interfaces between people and machines, and to automatically transcribe, extract, analyze, and route information from high-volume streams of spoken and written information. The workshops on Mathematical Foundations of Speech Processing and Natural Language Modeling were held in the Fall of 2000 at the University of Minnesota's NSF-sponsored Institute for Mathematics and Its Applications, as part of a "Mathematics in Multimedia" year-long program. Each workshop brought together researchers in the respective technologies on the one hand, and mathematicians and statisticians on the other hand, for an intensive week of cross-fertilization. There is a long history of benefit from introducing mathematical techniques and ideas to speech and language technologies. Examples include the source-channel paradigm, hidden Markov models, decision trees, exponential models and formal languages theory. It is likely that new mathematical techniques, or novel applications of existing techniques, will once again prove pivotal for moving the field forward. This volume consists of original contributions presented by participants during the two workshops. Topics include language modeling, prosody, acoustic-phonetic modeling, and statistical methodology.
Author : Dan Jurafsky
Publisher : Pearson Education India
ISBN 13 : 9788131716724
Total Pages : 912 pages
Book Rating : 4.7/5 (167 download)
Download or read book Speech & Language Processing written by Dan Jurafsky and published by Pearson Education India. This book was released on 2000-09 with total page 912 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Chin-Hui Lee
Publisher : Springer Science & Business Media
ISBN 13 : 1461313678
Total Pages : 524 pages
Book Rating : 4.4/5 (613 download)
Download or read book Automatic Speech and Speaker Recognition written by Chin-Hui Lee and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Joseph Keshet
Publisher : John Wiley & Sons
ISBN 13 : 9780470742037
Total Pages : 268 pages
Book Rating : 4.7/5 (42 download)
Download or read book Automatic Speech and Speaker Recognition written by Joseph Keshet and published by John Wiley & Sons. This book was released on 2009-04-27 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Javier Ramirez
Publisher : Bentham Science
ISBN 13 : 1608051722
Total Pages : 223 pages
Book Rating : 4.6/5 (8 download)
Download or read book Recent Advances in Robust Speech Recognition Technology written by Javier Ramirez and published by Bentham Science. This book was released on 2011 with total page 223 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This E-book is a collection of articles that describe advances in speech recognition technology. Robustness in speech recognition refers to the need to maintain high speech recognition accuracy even when the quality of the input speech is degraded, or whe"
Author : Jinyu Li
Publisher : Academic Press
ISBN 13 : 0128026162
Total Pages : 308 pages
Book Rating : 4.1/5 (28 download)
Download or read book Robust Automatic Speech Recognition written by Jinyu Li and published by Academic Press. This book was released on 2015-10-30 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Author : Uday Kamath
Publisher : Springer
ISBN 13 : 3030145964
Total Pages : 640 pages
Book Rating : 4.0/5 (31 download)
Download or read book Deep Learning for NLP and Speech Recognition written by Uday Kamath and published by Springer. This book was released on 2019-06-10 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Mark Johnson
Publisher : Springer Science & Business Media
ISBN 13 : 9780387203263
Total Pages : 304 pages
Book Rating : 4.2/5 (32 download)
Download or read book Mathematical Foundations of Speech and Language Processing written by Mark Johnson and published by Springer Science & Business Media. This book was released on 2004-03-18 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Speech and language technologies continue to grow in importance as they are used to create natural and efficient interfaces between people and machines, and to automatically transcribe, extract, analyze, and route information from high-volume streams of spoken and written information. The workshops on Mathematical Foundations of Speech Processing and Natural Language Modeling were held in the Fall of 2000 at the University of Minnesota's NSF-sponsored Institute for Mathematics and Its Applications, as part of a "Mathematics in Multimedia" year-long program. Each workshop brought together researchers in the respective technologies on the one hand, and mathematicians and statisticians on the other hand, for an intensive week of cross-fertilization. There is a long history of benefit from introducing mathematical techniques and ideas to speech and language technologies. Examples include the source-channel paradigm, hidden Markov models, decision trees, exponential models and formal languages theory. It is likely that new mathematical techniques, or novel applications of existing techniques, will once again prove pivotal for moving the field forward. This volume consists of original contributions presented by participants during the two workshops. Topics include language modeling, prosody, acoustic-phonetic modeling, and statistical methodology.
Author : Kamil Ekštein
Publisher : Springer Nature
ISBN 13 : 3030279472
Total Pages : 425 pages
Book Rating : 4.0/5 (32 download)
Download or read book Text, Speech, and Dialogue written by Kamil Ekštein and published by Springer Nature. This book was released on 2019-09-02 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 22nd International Conference on Text, Speech, and Dialogue, TSD 2019, held in Ljubljana, Slovenia, in September 2019. The 33 full papers presented in this volume were carefully reviewed and selected from 73 submissions. They were organized in topical sections named text and speech. The book also contains one invited talk in full paper length.
