Statistical Methods For Speech Recognition
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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
Connectionist Speech Recognition
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Author : Hervé A. Bourlard
language : en
Publisher: Springer Science & Business Media
Release Date : 1994
Connectionist Speech Recognition written by Hervé A. Bourlard 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 1994 with Computers categories.
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.
Statistical Pronunciation Modeling For Non Native Speech Processing
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Author : Rainer E. Gruhn
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-05-08
Statistical Pronunciation Modeling For Non Native Speech Processing written by Rainer E. Gruhn 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 2011-05-08 with Technology & Engineering categories.
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.
Springer Handbook Of Speech Processing
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Author : Jacob Benesty
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-11-28
Springer Handbook Of Speech Processing written by Jacob Benesty 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 2007-11-28 with Technology & Engineering categories.
This handbook plays a fundamental role in sustainable progress in speech research and development. With an accessible format and with accompanying DVD-Rom, it targets three categories of readers: graduate students, professors and active researchers in academia, and engineers in industry who need to understand or implement some specific algorithms for their speech-related products. It is a superb source of application-oriented, authoritative and comprehensive information about these technologies, this work combines the established knowledge derived from research in such fast evolving disciplines as Signal Processing and Communications, Acoustics, Computer Science and Linguistics.
Continuous Speech Recognition By Statistical Methods
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Author : Frederick Jelinek
language : en
Publisher:
Release Date : 1976
Continuous Speech Recognition By Statistical Methods written by Frederick Jelinek and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976 with categories.
Computational And Statistical Methods For Analysing Big Data With Applications
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Author : Shen Liu
language : en
Publisher: Academic Press
Release Date : 2015-11-20
Computational And Statistical Methods For Analysing Big Data With Applications written by Shen Liu and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-20 with Mathematics categories.
Due to the scale and complexity of data sets currently being collected in areas such as health, transportation, environmental science, engineering, information technology, business and finance, modern quantitative analysts are seeking improved and appropriate computational and statistical methods to explore, model and draw inferences from big data. This book aims to introduce suitable approaches for such endeavours, providing applications and case studies for the purpose of demonstration. Computational and Statistical Methods for Analysing Big Data with Applications starts with an overview of the era of big data. It then goes onto explain the computational and statistical methods which have been commonly applied in the big data revolution. For each of these methods, an example is provided as a guide to its application. Five case studies are presented next, focusing on computer vision with massive training data, spatial data analysis, advanced experimental design methods for big data, big data in clinical medicine, and analysing data collected from mobile devices, respectively. The book concludes with some final thoughts and suggested areas for future research in big data. - Advanced computational and statistical methodologies for analysing big data are developed - Experimental design methodologies are described and implemented to make the analysis of big data more computationally tractable - Case studies are discussed to demonstrate the implementation of the developed methods - Five high-impact areas of application are studied: computer vision, geosciences, commerce, healthcare and transportation - Computing code/programs are provided where appropriate
A Guide To Statistical Methods And To The Pertinent Literature Literatur Zur Angewandten Statistik
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Author : Lothar Sachs
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
A Guide To Statistical Methods And To The Pertinent Literature Literatur Zur Angewandten Statistik written by Lothar Sachs 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 Mathematics categories.
Readers of my books, students and scientists, often ask for spe cial references not commonly found in introductory or interme diate books on statistics. From the titles and contents of 1449 key papers and books which are listed and numbered in Sec tion 5, I have selected keywords and subject headings and ar ranged them alphabetically together with the numbers of perti nent references in Section 3. Number 1153, for instance, denotes my book" Applied Statis tics". It contains a bibliographical section on pages 568 to 641. Supplementary material is displayed in this small bibliographi cal guide. It also complements well-known textbooks of Box, Hunter and Hunter (No.121), Dixon and Massey (No.286), Snedecor and Cochran (No. 1238), and many recent competitors. Since the methodology of statistics is expanding rapidly, many methods are not considered at all or only introduced in the basic textbooks of statistics. There is a need for intermediate statistical methods concerned with increasingly complicated ap plications of statistics to actual research situations. Here the specification of terms helps to find some sources. Since the ref erences vary considerably in length and content, the number of culled or extracted terms per referenced page varies even more, as does also their degree of specialization; however in most cases an intermediate statistical level is maintained.
Statistical Methods And Reasoning For The Clinical Sciences
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Author : Eiki Satake
language : en
Publisher: Plural Publishing
Release Date : 2014-08-01
Statistical Methods And Reasoning For The Clinical Sciences written by Eiki Satake and has been published by Plural Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-01 with Medical categories.
Statistical Methods And Models For Video Based Tracking Modeling And Recognition
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Author : Rama Chellappa
language : en
Publisher: Now Publishers Inc
Release Date : 2010
Statistical Methods And Models For Video Based Tracking Modeling And Recognition written by Rama Chellappa and has been published by Now Publishers Inc this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.
Computer vision systems attempt to understand a scene and its components from mostly visual information. The geometry exhibited by the real world, the influence of material properties on scattering of incident light, and the process of imaging introduce constraints and properties that are key to solving some of these tasks. In the presence of noisy observations and other uncertainties, the algorithms make use of statistical methods for robust inference. In this paper, we highlight the role of geometric constraints in statistical estimation methods, and how the interplay of geometry and statistics leads to the choice and design of algorithms. In particular, we illustrate the role of imaging, illumination, and motion constraints in classical vision problems such as tracking, structure from motion, metrology, activity analysis and recognition, and appropriate statistical methods used in each of these problems.
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.