Pattern Recognition in Speech and Language Processing

by Wu Chou (Editor), Biing-Hwang Juang (Editor)

Overview

Over the last 20 years, approaches to designing speech and language processing algorithms have moved from methods based on linguistics and speech science to data-driven pattern recognition techniques. These techniques have been the focus of intense, fast-moving research and have contributed to significant advances in this field. Pattern Reco

Product Details

ISBN-13:	9781135702250
Publisher:	CRC Press
Publication date:	02/26/2003
Series:	Electrical Engineering & Applied Signal Processing Series
Sold by:	Barnes & Noble
Format:	eBook
Pages:	416
File size:	4 MB

About the Author

Wu Chou, Biing-Hwang Juang

Table of Contents

FUNDAMENTALS AND RECENT ADVANCES IN PATTERN RECOGNITION: Classifier Design Criteria and Discriminant Function Approach in Speech and Language Processing. Minimum Bayes-Risk Automatic Speech Recognition. A Decision Theoretic Formulation for Adaptive and Robust Automatic Speech Recognition. Speech Pattern Recognition Using Neural Networks, Distributed Recognizers, and Decision Fusion.PATTERN RECOGNITION IN SPEECH AND AUDIO PROCESSING: Maximum Mutual Information Training of Hidden Markov Models. Large Vocabulary Speech Recognition Based on Statistical Methods. Toward Spontaneous Speech Recognition. Speaker Authentication. PATTERN RECOGNITION IN LANGUAGE PROCESSING: HMMs Applied Top Language Processing Problems. Statistical Language Models with Embedded Latent Semantic Knowledge. Semantic Information Processing of Spoken Language. Machine Translation Using Stochastic Modeling. Explicit Event Modeling for Topic Detection and Tracking in Broadcast News.