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

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

Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition Hardback - 2000

by Jurafsky, Daniel & James H. Martin

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Upper Saddle River, NJ: Prentice-Hall, Inc, 2000 WYSIWYG pricing--no added shipping charge for standard shipping within USA. White laminated boards, blue & black titles & decorations, xxvi, 934 pp, bibliography, index. Contents: words (regular expressions & automata; morphology & finite-state transducers; computational phonology & text-to-speech; probabilistic models of pronunciation & spelling; n-grams; HMMs & speech recognition); syntax (word classes & part-of-speech tagging; context-free grammars for English; parsing with context-free grammars; features & unification; lexicalized & probabilistic parsing; language & complexity); semantics (representing meaning; semantic analysis; lexical semantics; word sense disambiguation & information retrieval); pragmatics (discourse; dialogue & conversational agents; natural language generation; machine translation). Appendices: regular expression operators; the Porter stemming algorithm; C5 & C7 tagsets; training HMMs: the forward-backward algorithm. Shipping weight 4 lbs.. First Edition. . Fine/No DJ. 24 X 18 cm.
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Reader reviews for Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition

From the publisher

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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