Robust Speech Recognition of Uncertain or Missing Data

Theory and Applications

Editors: Kolossa, Dorothea, Haeb-Umbach, Reinhold (Eds.)

  • Scientists and researchers in the field of speech recognition will find an overview of the state of the art in robust speech recognition.
  • Professionals working in speech recognition will find strategies for improving results in various conditions of mismatch.
  • The contributing authors are among the leading researchers in this field.
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About this book

Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition.

The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models.

 

About the authors

Prof. Dr.-Ing. Dorothea Kolossa is a professor at the Institut für Kommunikationsakustik of the Ruhr-Universität Bochum, Germany; her research interests are automatic speech recognition, digital speech signal processing, and blind source separation.

Prof. Dr.-Ing. Reinhold Haeb-Umbach heads the Dept. of Communications Engineering of the University of Paderborn, Germany; his research interest are speech signal processing and automatic speech recognition, statistical learning and pattern recognition, and signal processing for digital communications.

 

Table of contents (13 chapters)

  • Introduction

    Haeb-Umbach, Reinhold (et al.)

    Pages 1-5

  • Uncertainty Decoding and Conditional Bayesian Estimation

    Haeb-Umbach, Reinhold

    Pages 9-33

  • Uncertainty Propagation

    Astudillo, Ramón Fernandez (et al.)

    Pages 35-64

  • Front-End, Back-End, and Hybrid Techniques for Noise-Robust Speech Recognition

    Deng, Li

    Pages 67-99

  • Model-Based Approaches to Handling Uncertainty

    Gales, M. J. F.

    Pages 101-125

Buy this book

eBook $119.00
price for USA
  • ISBN 978-3-642-21317-5
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $159.00
price for USA
  • ISBN 978-3-642-21316-8
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $159.00
price for USA
  • ISBN 978-3-642-43868-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Rent the ebook  
  • Rental duration: 1 or 6 month
  • low-cost access
  • online reader with highlighting and note-making option
  • can be used across all devices
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Bibliographic Information

Bibliographic Information
Book Title
Robust Speech Recognition of Uncertain or Missing Data
Book Subtitle
Theory and Applications
Editors
  • Dorothea Kolossa
  • Reinhold Haeb-Umbach
Copyright
2011
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-21317-5
DOI
10.1007/978-3-642-21317-5
Hardcover ISBN
978-3-642-21316-8
Softcover ISBN
978-3-642-43868-4
Edition Number
1
Number of Pages
XVIII, 380
Topics