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Hierarchical Neural Network Structures for Phoneme Recognition

  • Book
  • © 2013

Overview

Authors:
  1. Daniel Vasquez

    1. , Institute of Information Technology, University of Ulm, Ulm, Germany

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  2. Rainer Gruhn

    1. SVOX Deutschland GmbH, Ulm, Germany

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  3. Wolfgang Minker

    1. , Institute of Information Technology, University of Ulm, Ulm, Germany

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  • 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)

  1. Front Matter

    Pages 1-15
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  2. Introduction

    • Daniel Vasquez, Rainer Gruhn, Wolfgang Minker
    Pages 1-6

  3. Background in Speech Recognition

    • Daniel Vasquez, Rainer Gruhn, Wolfgang Minker
    Pages 7-30

  4. Phoneme Recognition Task

    • Daniel Vasquez, Rainer Gruhn, Wolfgang Minker
    Pages 31-48

  5. Hierarchical Approach and Downsampling Schemes

    • Daniel Vasquez, Rainer Gruhn, Wolfgang Minker
    Pages 49-59

  6. Extending the Hierarchical Scheme: Inter and Intra Phonetic Information

    • Daniel Vasquez, Rainer Gruhn, Wolfgang Minker
    Pages 61-101

  7. Theoretical Framework for Phoneme Recognition Analysis

    • Daniel Vasquez, Rainer Gruhn, Wolfgang Minker
    Pages 103-117

  8. Summary and Conclusions

    • Daniel Vasquez, Rainer Gruhn, Wolfgang Minker
    Pages 119-122

  9. Back Matter

    Pages 0--1
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Keywords

About this book

In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are mainly evaluated within the phoneme recognition task under the Hybrid Hidden Markov Model/Artificial Neural Network (HMM/ANN) paradigm. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron (MLP). Additionally, the output of the first level is used as an input for the second level. This system can be substantially speeded up by removing the redundant information contained at the output of the first level.

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

  • , Institute of Information Technology, University of Ulm, Ulm, Germany

    Daniel Vasquez, Wolfgang Minker

  • SVOX Deutschland GmbH, Ulm, Germany

    Rainer Gruhn

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