Authors:
- Includes an overview on the state of art
- Gives an approach for In-Car Applications
- Written for professionals and practitioners in that field
Part of the book series: Signals and Communication Technology (SCT)
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Table of contents (8 chapters)
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Front Matter
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Back Matter
About this book
Current speech recognition systems are based on speaker independent speech models and suffer from inter-speaker variations in speech signal characteristics. This work develops an integrated approach for speech and speaker recognition in order to gain space for self-learning opportunities of the system. This work introduces a reliable speaker identification which enables the speech recognizer to create robust speaker dependent models In addition, this book gives a new approach to solve the reverse problem, how to improve speech recognition if speakers can be recognized. The speaker identification enables the speaker adaptation to adapt to different speakers which results in an optimal long-term adaptation.
Authors and Affiliations
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Institute of Information Technology, University of Ulm, Ulm, Germany
Tobias Herbig, Wolfgang Minker
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Dept. Speech Recognition, Harman Becker Automotive Systems GmbH, Ulm, Germany
Franz Gerl
Bibliographic Information
Book Title: Self-Learning Speaker Identification
Book Subtitle: A System for Enhanced Speech Recognition
Authors: Tobias Herbig, Franz Gerl, Wolfgang Minker
Series Title: Signals and Communication Technology
DOI: https://doi.org/10.1007/978-3-642-19899-1
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2011
Hardcover ISBN: 978-3-642-19898-4Published: 18 June 2011
Softcover ISBN: 978-3-642-26880-9Published: 03 August 2013
eBook ISBN: 978-3-642-19899-1Published: 18 June 2011
Series ISSN: 1860-4862
Series E-ISSN: 1860-4870
Edition Number: 1
Number of Pages: XII, 172
Topics: Signal, Image and Speech Processing, Biometrics, Communications Engineering, Networks, User Interfaces and Human Computer Interaction