SPEECH and LANGUAGE PROCESSING

An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition

"This is quite simply the most complete introduction to natural language and speech technology ever written."

-Richard Sproat, AT&T Labs-Resran

"This book is impressive in its scope and depth. It has the potential to accomplish an unlikely feat to convey the intricacy, ingenuity, and beauty found in both the human language and in many approaches devised for language processing. 1 expect it to become a standard text in the field."

Andreas Stolcke. SRI International

U J This book offers a unified vision of speech and language processing, presenting state-of-the-art algorithms and techniques for both speech and text-based processing of natural language. This comprehensive work covers both statistical and symbolic approaches to language processing, it shows how they can be applied to important tasks such as speech recognition, spelling and grammar correction, information extraction, search engines, machine translation, and the creation of spoken-language dialog agents. The following distinguishing features make the text both an introduction to the field and an advanced reference guide.

DISTINGUISHING FEATURES:

UNIFIED AND COMPREHENSIVE COVERAGE OF THE FIELD

Covers the fundamental algorithms of each field, whether proposed for spoken or written language, whether logical or statistical in origin.

EMPHASIS ON WEB AND OTHER PRACTICAL APPLICATIONS

Gives readers an understanding of how language-related algorithms can be applied to important real-world problems.

EMPHASIS ON SCIENTIFIC EVALUATION

Offers a description of how systems are evaluated with each problem domain.

EMPIRICIST/STATISTICAL/MACHINE LEARNING APPROACHES TO LANGUAGE PROCESSING

Covers all of the new statistical approaches, while still completely covering the earlier more structured and rule based methods.

ABOUT THE AUTHORS:

Daniel Jurafsky received his Ph.D. in Computer Science from the University of California at Berkeley. He then joined the faculty of the Department of Linguistics, Department of Computer Science, and the Institute of Cognitive Science at the University of Colorado at Boulder. His research focuses on combining linguistic knowledge with probabilistic models of language and speech processing in humans and machines. In 1997, he received the NSF Career Award for his work in speech and language processing.

James H. Martin received his Ph.D. in Computer Science from the University of California at Berkeley. He then joined the faculty of the Department of Computer Science and the Institute of Cognitive Science at the University of Colorado at Boulder. His research interests include computational semantics, metaphor, machine learning, and information retrieval. He has published over 40 papers and one previous book, A Computational Model of Metaphor Interpretation (Academic Press, 1990).

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