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Connectionist Speech Recognition : A Hybrid Approach - Herve Bourlard

Connectionist Speech Recognition

A Hybrid Approach

Hardcover

Published: 31st October 1993
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Connectionist Speech Recognition: A Hybrid Approach describes the theory and implementation of a method to incorporate neural network approaches into state of the art continuous speech recognition systems based on hidden Markov models (HMMs) to improve their performance. In this framework, neural networks (and in particular, multilayer perceptrons or MLPs) have been restricted to well-defined subtasks of the whole system, i.e. HMM emission probability estimation and feature extraction.
The book describes a successful five-year international collaboration between the authors. The lessons learned form a case study that demonstrates how hybrid systems can be developed to combine neural networks with more traditional statistical approaches. The book illustrates both the advantages and limitations of neural networks in the framework of a statistical systems.
Using standard databases and comparison with some conventional approaches, it is shown that MLP probability estimation can improve recognition performance. Other approaches are discussed, though there is no such unequivocal experimental result for these methods.
Connectionist Speech Recognition is of use to anyone intending to use neural networks for speech recognition or within the framework provided by an existing successful statistical approach. This includes research and development groups working in the field of speech recognition, both with standard and neural network approaches, as well as other pattern recognition and/or neural network researchers. The book is also suitable as a text for advanced courses on neural networks or speech processing.

List of Figures
List of Tables
Notation
Foreword
Preface
Background
Introduction
Statistical Pattern Classification
Hidden Markov Models
Multilayer Perceptions
Hybrid HMM/MLP Systems
Speech Recognition using ANNs
Statistical Inference in MLPs
The Hybrid HMM/MLP Approach
Experimental Systems
Context-Dependent MPLs
System Tradeoffs
Training Hardware and Software
Additional Topics
Cross-Validation in MLP Training
HMM/MLP and Predictive Models
Feature Extraction by MLP
Finale
Final System Overview
Conclusions
Bibliography
Index
Acronyms
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9780792393962
ISBN-10: 0792393961
Series: The Springer International Series in Engineering and Computer Science
Audience: Professional
Format: Hardcover
Language: English
Number Of Pages: 313
Published: 31st October 1993
Publisher: Springer
Country of Publication: NL
Dimensions (cm): 23.5 x 15.5  x 2.69
Weight (kg): 1.47