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.
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.