Pattern Recognition in Speech and Language Processing

Series:
Electrical Engineering & Applied Signal Processing Series
Published:
February 26, 2003 by CRC Press - 416 Pages
Editor(s):
Wu Chou, Avaya Labs Research, Basking Ridge, New Jersey, USA; Biing-Hwang Juang, Georgia Institute of Technology, Atlanta, USA

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Hardback
$209.95
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ISBN 9780849312328
Cat# 1232
 

Features

  • Provides comprehensive coverage of recent advances in applying pattern recognition to real speech and audio processing systems
  • Presents results tabulated and organized to convey a full understanding of the discussed approaches
  • Includes numerous examples of practical applications and systems
  • Comprises chapters contributed by leading experts in the field designed to be comprehensible to anyone with a general background in pattern recognition
  • Includes a comprehensive list of references and a survey of state-of-the-art technologies

    • Summary

    Over the last 20 years, approaches to designing speech and language processing algorithms have moved from methods based on linguistics and speech science to data-driven pattern recognition techniques. These techniques have been the focus of intense, fast-moving research and have contributed to significant advances in this field.

    Pattern Recognition in Speech and Language Processing offers a systematic, up-to-date presentation of these recent developments. It begins with the fundamentals and recent theoretical advances in pattern recognition, with emphasis on classifier design criteria and optimization procedures. The focus then shifts to the application of these techniques to speech processing, with chapters exploring advances in applying pattern recognition to real speech and audio processing systems. The final section of the book examines topics related to pattern recognition in language processing: topics that represent promising new trends with direct impact on information processing systems for the Web, broadcast news, and other content-rich information resources.

    Each self-contained chapter includes figures, tables, diagrams, and references. The collective effort of experts at the forefront of the field, Pattern Recognition in Speech and Language Processing offers in-depth, insightful discussions on new developments and contains a wealth of information integral to the further development of human-machine communications.

    Table of Contents

    Minimum Classification Error (MSE) Approach in Pattern Recognition, Wu Chou
    Minimum Bayes-Risk Methods in Automatic Speech Recognition, Vaibhava Goel and William Byrne
    A Decision Theoretic Formulation for Adaptive and Robust Automatic Speech Recognition, Qiang Huo
    Speech Pattern Recognition Using Neural Networks, Shigeru Katagiri
    Large Vocabulary Speech Recognition Based on Statistical Methods, Jean-Luc Gauvain
    Toward Spontaneous Speech Recognition and Understanding, Sadaoki Furui
    Speaker Authentication, Qi Li and Biing-Hwang Juang
    HMMs for Language Processing Problems, Richard M. Schwartz and John Makhoul
    Statistical Language Models with Embedded Latent Semantic Knowledge, Jerome R. Bellegarda
    Semantic Information Processing of Spoken Language - How May I Help You?sm, A.L. Gorin, A. Abella, T. Alonso, G . Riccardi, and J.H. Wright
    Machine Translation Using Statistical Modeling, H. Ney and F.J. Och
    Modeling Topics for Detection and Tracking, James Allen

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