Authors:
- Simplifies the analysis in spoken language dialogue systems
- Investigates hierarchical structures based on neural networks for automatic speech recognition
- Written for academic and industrial researchers in speech recognition
Part of the book series: Signals and Communication Technology (SCT)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
About this book
Reviews
From the reviews:
“This brief book comes packed with useful information about some novel techniques for the recognition of speech building blocks known as phonemes. … it is brimming with useful and well-presented information. I recommend it for graduate students in the field, as well as for practicing professionals.” (Vladimir Botchev, Computing Reviews, May, 2013)Authors and Affiliations
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, Institute of Information Technology, University of Ulm, Ulm, Germany
Daniel Vasquez, Wolfgang Minker
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SVOX Deutschland GmbH, Ulm, Germany
Rainer Gruhn
Bibliographic Information
Book Title: Hierarchical Neural Network Structures for Phoneme Recognition
Authors: Daniel Vasquez, Rainer Gruhn, Wolfgang Minker
Series Title: Signals and Communication Technology
DOI: https://doi.org/10.1007/978-3-642-34425-1
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Berlin Heidelberg 2013
Hardcover ISBN: 978-3-642-34424-4Published: 18 October 2012
Softcover ISBN: 978-3-642-43210-1Published: 09 November 2014
eBook ISBN: 978-3-642-34425-1Published: 17 October 2012
Series ISSN: 1860-4862
Series E-ISSN: 1860-4870
Edition Number: 1
Number of Pages: XVIII, 134
Topics: Signal, Image and Speech Processing, User Interfaces and Human Computer Interaction, Computational Intelligence, Natural Language Processing (NLP)