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Speaker Classification I

Fundamentals, Features, and Methods

  • Editors
  • Christian Müller

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4343)

Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 4343)

Table of contents

  1. Front Matter
  2. Fundamentals

  3. Characteristics

    1. Tanja Schultz
      Pages 47-74
    2. Ulrike Gut
      Pages 75-87
    3. Susanne Schötz
      Pages 88-107
    4. John H. L. Hansen, Sanjay Patil
      Pages 108-137
    5. Anton Batliner, Richard Huber
      Pages 138-151
    6. Erik J. Eriksson, Robert D. Rodman, Robert C. Hubal
      Pages 152-173
  4. Applications

  5. Methods and Features

    1. Stefan Schacht, Jacques Koreman, Christoph Lauer, Andrew Morris, Dalei Wu, Dietrich Klakow
      Pages 226-240
    2. Elizabeth Shriberg
      Pages 241-259
    3. Jacques Koreman, Dalei Wu, Andrew C. Morris
      Pages 260-277
    4. D. E. Sturim, W. M. Campbell, D. A. Reynolds
      Pages 278-297
  6. Evaluation

  7. Back Matter

About this book

Introduction

As well as conveying a message in words and sounds, the speech signal carries information about the speaker's own anatomy, physiology, linguistic experience and mental state. These speaker characteristics are found in speech at all levels of description: from the spectral information in the sounds to the choice of words and utterances themselves.

This volume and its companion volume, LNAI 4441, constitute a state-of-the-art survey for the field of speaker classification. They approach the following questions: What characteristics of the speaker become manifest in his or her voice and speaking behavior? Which of them can be inferred from analyzing the acoustic realizations? What can this information be used for? Which methods are the most suitable for diversified problems in this area of research? How should the quality of the results be evaluated?

The 19 contributions to this volume comprise general and overview-like articles that are organized in topical sections on fundamentals, characteristics, applications, methods and features, as well as evaluation.

Keywords

Acoustics Information acoustic analysis acoustic correlates authentication classification cognition face recognition feature extraction higher-order statistics identification language recognition modeling speaker characteristics verification

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-74200-5
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-74186-2
  • Online ISBN 978-3-540-74200-5
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site
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