Mathematical Foundations Of Speech And Language Processing
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Mathematical Foundations Of Speech And Language Processing
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Author : Mark Johnson
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Mathematical Foundations Of Speech And Language Processing written by Mark Johnson 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 2012-12-06 with Technology & Engineering categories.
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.
Speech And Language Processing
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Author : Daniel Jurafsky
language : en
Publisher:
Release Date : 2000-01
Speech And Language Processing written by Daniel Jurafsky and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01 with Automatic speech recognition categories.
This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing.
Foundations Of Statistical Natural Language Processing
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Author : Christopher Manning
language : en
Publisher: MIT Press
Release Date : 1999-05-28
Foundations Of Statistical Natural Language Processing written by Christopher Manning and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-05-28 with Language Arts & Disciplines categories.
Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.
Statistical Methods For Speech Recognition
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Author : Frederick Jelinek
language : en
Publisher: MIT Press
Release Date : 2022-11-01
Statistical Methods For Speech Recognition written by Frederick Jelinek and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-01 with Language Arts & Disciplines categories.
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
Handbook Of Signal Processing In Acoustics
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Author : David Havelock
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-10-26
Handbook Of Signal Processing In Acoustics written by David Havelock 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 2008-10-26 with Science categories.
The Handbook of Signal Processing in Acoustics brings together a wide range of perspectives from over 100 authors to reveal the interdisciplinary nature of the subject. It brings the key issues from both acoustics and signal processing into perspective and is a unique resource for experts and practitioners alike to find new ideas and techniques within the diversity of signal processing in acoustics.
Introducing Speech And Language Processing
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Author : John S. Coleman
language : en
Publisher: Cambridge University Press
Release Date : 2005-03-03
Introducing Speech And Language Processing written by John S. Coleman and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-03-03 with Computers categories.
This major new textbook provides a clearly-written, concise and accessible introduction to speech and language processing. Assuming knowledge of only the very basics of linguistics and written specifically for students with no technical background, it is the perfect starting point for anyone beginning to study the discipline. Student s are shown from an elementary level how to use two programming languages, C and Prolog, and the accompanying CD-ROM contains all the software needed. Setting an invaluable foundation for further study, this is set to become the leading introduction to the field.
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.
Mathematics For Machine Learning
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Author : Marc Peter Deisenroth
language : en
Publisher: Cambridge University Press
Release Date : 2020-04-23
Mathematics For Machine Learning written by Marc Peter Deisenroth and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-23 with Computers categories.
Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.
Speech And Audio Processing For Coding Enhancement And Recognition
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Author : Tokunbo Ogunfunmi
language : en
Publisher: Springer
Release Date : 2014-10-14
Speech And Audio Processing For Coding Enhancement And Recognition written by Tokunbo Ogunfunmi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-14 with Technology & Engineering categories.
This book describes the basic principles underlying the generation, coding, transmission and enhancement of speech and audio signals, including advanced statistical and machine learning techniques for speech and speaker recognition with an overview of the key innovations in these areas. Key research undertaken in speech coding, speech enhancement, speech recognition, emotion recognition and speaker diarization are also presented, along with recent advances and new paradigms in these areas.
Log Linear Models Extensions And Applications
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Author : Aleksandr Aravkin
language : en
Publisher: MIT Press
Release Date : 2024-12-03
Log Linear Models Extensions And Applications written by Aleksandr Aravkin and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-03 with Computers categories.
Advances in training models with log-linear structures, with topics including variable selection, the geometry of neural nets, and applications. Log-linear models play a key role in modern big data and machine learning applications. From simple binary classification models through partition functions, conditional random fields, and neural nets, log-linear structure is closely related to performance in certain applications and influences fitting techniques used to train models. This volume covers recent advances in training models with log-linear structures, covering the underlying geometry, optimization techniques, and multiple applications. The first chapter shows readers the inner workings of machine learning, providing insights into the geometry of log-linear and neural net models. The other chapters range from introductory material to optimization techniques to involved use cases. The book, which grew out of a NIPS workshop, is suitable for graduate students doing research in machine learning, in particular deep learning, variable selection, and applications to speech recognition. The contributors come from academia and industry, allowing readers to view the field from both perspectives. Contributors Aleksandr Aravkin, Avishy Carmi, Guillermo A. Cecchi, Anna Choromanska, Li Deng, Xinwei Deng, Jean Honorio, Tony Jebara, Huijing Jiang, Dimitri Kanevsky, Brian Kingsbury, Fabrice Lambert, Aurélie C. Lozano, Daniel Moskovich, Yuriy S. Polyakov, Bhuvana Ramabhadran, Irina Rish, Dimitris Samaras, Tara N. Sainath, Hagen Soltau, Serge F. Timashev, Ewout van den Berg