Fundamentals of Speech Recognition
Author:   Lawrence Rabiner ,  Biing-Hwang Juang
Publisher:   Pearson Education (US)
Edition:   United States ed
ISBN:  

9780130151575


Pages:   544
Publication Date:   01 May 1993
Format:   Paperback
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

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Fundamentals of Speech Recognition


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Overview

Provides a theoretically sound, technically accurate, and complete description of the basic knowledge and ideas that constitute a modern system for speech recognition by machine. KEY TOPICS: Covers production, perception, and acoustic-phonetic characterization of the speech signal; signal processing and analysis methods for speech recognition; pattern comparison techniques; speech recognition system design and implementation; theory and implementation of hidden Markov models; speech recognition based on connected word models; large vocabulary continuous speech recognition; and task- oriented application of automatic speech recognition. MARKET: For practicing engineers, scientists, linguists, and programmers interested in speech recognition.

Full Product Details

Author:   Lawrence Rabiner ,  Biing-Hwang Juang
Publisher:   Pearson Education (US)
Imprint:   Prentice Hall
Edition:   United States ed
Dimensions:   Width: 18.00cm , Height: 3.00cm , Length: 23.50cm
Weight:   0.856kg
ISBN:  

9780130151575


ISBN 10:   0130151572
Pages:   544
Publication Date:   01 May 1993
Audience:   College/higher education ,  Tertiary & Higher Education
Format:   Paperback
Publisher's Status:   Out of Print
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

Table of Contents

1. Fundamentals of Speech Recognition. 2. The Speech Signal: Production, Perception, and Acoustic-Phonetic Characterization. 3. Signal Processing and Analysis Methods for Speech Recognition. 4. Pattern Comparison Techniques. 5. Speech Recognition System Design and Implementation Issues. 6. Theory and Implementation of Hidden Markov Models. 7. Speech Recognition Based on Connected Word Models. 8. Large Vocabulary Continuous Speech Recognition. 9. Task-Oriented Applications of Automatic Speech Recognition.

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