Robust Speech Recognition of Uncertain or Missing Data. Theory and Applications.

Kolossa, Dorothea; Haeb-Umbach, Reinhold (Eds.)

ISBN 10: 3642213162 / ISBN 13: 9783642213168

Published by Berlin, Springer., 2011

About this Item

XVIII, 380 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. Stamped. Sprache: Englisch.

Seller Inventory # 190BB

Bibliographic Details

• Title: Robust Speech Recognition of Uncertain or Missing Data. Theory and Applications.
• Publisher: Berlin, Springer.
• Publication Date: 2011
• Language: English
• ISBN 10: 3642213162
• ISBN 13: 9783642213168
• Binding: Hardcover
• Seller catalogs:
  • Technik

About this title

Synopsis

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 Author

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.