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

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Prentice Hall, 2000 - Language Arts & Disciplines - 934 pages
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This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corporations.* Each chapter is built around one or more worked examples demonstrating the main idea of the chapter. * Uses worked examples to illustrate the relative strengths and weaknesses of various approaches. * Methodology boxes - Included in each chapter. * Introduces important methodological tools such as evaluation, wizard of oz techniques, etc. * Problem sets - Included in each chapter. * Integration of speech and text processing - Merges speech processing and natural language processing fields. * 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. * Includes modern rigorous evaluation metrics. * Unified and comprehensive coverage of the field - Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language. * Shows students how the same algorithm can be used for speech recognition and word-sense disambiguation. * Emphasis on Web and oth

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Contents

Introduction
1
Introduction
14
Words
19
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About the author (2000)

Daniel Jurafsky 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.

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