Fundamentals of Speech Recognition [Paperback]

Lawrence Rabiner (Author), Biing-Hwang Juang (Author)

Book Description

ISBN-10: 0130151572 | ISBN-13: 978-0130151575 | Publication Date: April 22, 1993 | Edition: 1

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. For practicing engineers, scientists, linguists, and programmers interested in speech recognition.

Editorial Reviews

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 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. For practicing engineers, scientists, linguists, and programmers interested in speech recognition.

Product Details

• Paperback: 496 pages
• Publisher: Prentice Hall; 1 edition (April 22, 1993)
• Language: English
• ISBN-10: 0130151572
• ISBN-13: 978-0130151575
• Product Dimensions: 9.3 x 6.9 x 1.2 inches
• Shipping Weight: 1.9 pounds (View shipping rates and policies)
• Average Customer Review: 4.4 out of 5 stars  See all reviews (7 customer reviews)
• Amazon Best Sellers Rank: #736,518 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

10 of 10 people found the following review helpful:

5.0 out of 5 stars Excellent Introduction, December 9, 2001

By 

Optimistix (New York City) - See all my reviews

This review is from: Fundamentals of Speech Recognition (Paperback)

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 author of the first widely-read tutorial on HMMs, so
naturally the presentation of HMMs is one of the strong points of this
textbook. The theory is developed in detail, but in an easy to follow
fashion, starting with the very basics and with plenty of helpful examples.
The implementation is discussed at great length as well, starting with
the simplest of tasks and progressing to the state-of-the-art (circa 1993).

That isn't to say that HMMs are the only good part of this book - indeed,
practically every topic, whether it be perception, transforms, vector quantization
or dynamic programming, is presented with great clarity. This book really is easy to
learn from, with numerous examples and illustrations.

The field of speech recognition is inherently multi-disciplinary in nature,
drawing upon various areas of study, including Physics, Physiology, Acoustics,
Signal Processing and Computer Science, to name but a few. The authors do a
great job of explaining all these facets, as well as the mathematics that
is an essential tool.

The only caveat is that it's now a little old (published 1993), since the
field has been growing by leaps and bounds - so while the basics remain
the same, things have changed and hence what's said here should not be
taken as the last word on the subject.

Perhaps a new edition is due, and would certainly be most welcome.

However, for an excellent, accessible introduction to this exciting field,
this is still a great choice.

10 of 10 people found the following review helpful:

5.0 out of 5 stars Hidden Markov Modeling primer, December 7, 1998

By A Customer

This review is from: Fundamentals of Speech Recognition (Paperback)

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.

5 of 6 people found the following review helpful:

4.0 out of 5 stars Good introduction for beginners, March 1, 2000

By 

Olivier Pietquin - See all my reviews

This review is from: Fundamentals of Speech Recognition (Paperback)

The beginner in Automaitc Speech Recognition should read this book. It introduces all the basics of signal processing and vocal tract modeling needed and provides good descriptions of modern algorithms for statistical speech recognition (such as dynamic programmation, Hidden Markov Models, Viterbi Algorithm ...).