Fundamentals of Speech Recognition
| Author | : | |
| Rating | : | 4.24 (544 Votes) |
| Asin | : | 0130151572 |
| Format Type | : | paperback |
| Number of Pages | : | 496 Pages |
| Publish Date | : | 2014-02-21 |
| Language | : | English |
DESCRIPTION:
For practicing engineers, scientists, linguists, and programmers interested in speech recognition. From the Back Cover 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. 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 implemen
"Five Stars" according to Thomas Quintana. Everything went very smooth.. Excellent Introduction This book is a comprehensive and excellent introduction to the ever-expanding field of Automatic Speech Recognition. Starting with models of speech production, speech characterization, methods of analysis (transforms etc), the authors go onto discuss pattern comparison, hidden Markov models (HMMs), and design and implementation of speech recognition systems, right from isolated word recognition to large vocabulary continuous speech recognition systems. Neural networks and their use in speech recognition is also presented, though somewhat briefly. Rabiner was the a. "Hidden Markov Modeling primer" according to A Customer. The book is focused on extraction of attributes of human speech with modern digital and mathematical tools. In Rabiner's approach, an essential element is the Hidden Markov Model and its ability to predict the state of a non-observable system. HM models are the topic of sophisticated techniques and study, and so independent fundamental description of the methods are infrequent. Rabiner goes out of his way to clearly define the HMM before addressing its specific application to speech processing. A very useful introduction to the HMM.
For practicing engineers, scientists, linguists, and programmers interested in speech recognition.. 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. 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