Statistical Methods for Speech Recognition / Edition 1

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Overview

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.

Incl. basic language modeling; the expectation-maximization algorithm and its consequences; triphones & allophones etc.

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What People Are Saying

From the Publisher
"For the first time, researchers in this field will have a bookthat will serve as the bible' for many aspects of language andspeech processing. Frankly, I can't imagine a person working in thisfield not wanting to have a personal copy." Victor Zue , MIT Laboratory for Computer Science
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Product Details

  • ISBN-13: 9780262100663
  • Publisher: MIT Press
  • Publication date: 1/16/1998
  • Series: Language, Speech, and Communication
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 305
  • Product dimensions: 6.20 (w) x 9.00 (h) x 1.00 (d)

Table of Contents

Preface
Ch. 1 The Speech Recognition Problem 1
Ch. 2 Hidden Markov Models 15
Ch. 3 The Acoustic Model 39
Ch. 4 Basic Language Modeling 57
Ch. 5 The Viterbi Search 79
Ch. 6 Hypothesis Search on a Three and the Fast Match 93
Ch. 7 Elements of Information Theory 113
Ch. 8 The Complexity of Tasks - The Quality of Language Models 137
Ch. 9 The Expectation-Maximization Algorithm and its Consequences 147
Ch. 10 Decision Trees and Tree Language Models 165
Ch. 11 Phonetics from Orthography: Spelling-to-Base Form Mappings 197
Ch. 12 Triphones and Allophones 207
Ch. 13 Maximum Entropy Probability Estimation and Language Models 219
Ch. 14 Three Applications of Maximum Entropy Estimation to Language Modeling 245
Ch. 15 Estimation of Probabilities from Counts and the Back-Off Method 257
Name Index 275
Subject Index 279
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