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Product Identifiers
PublisherPearson Education
ISBN-100130950696
ISBN-139780130950697
eBay Product ID (ePID)1101471
Product Key Features
Number of Pages934 Pages
LanguageEnglish
Publication NameSpeech and Language Processing : An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition
Publication Year2000
SubjectComputer Vision & Pattern Recognition, Linguistics / General
TypeTextbook
Subject AreaComputers, Language Arts & Disciplines
AuthorJames H. Martin, Daniel Jurafsky
FormatHardcover
Dimensions
Item Height1.5 in
Item Weight52 Oz
Item Length9.5 in
Item Width7.3 in
Additional Product Features
Intended AudienceCollege Audience
LCCN99-087845
Dewey Edition22
IllustratedYes
Dewey Decimal410.2/85
Table Of Content1. Introduction. I. WORDS. 2. Regular Expressions and Automata. 3. Morphology and Finite-State Transducers. 4. Computational Phonology and Text-to-Speech. 5. Probabilistic Models of Pronunciation and Spelling. 6. N-grams. 7. HMMs and Speech Recognition. II. SYNTAX. 8. Word Classes and Part-of-Speech Tagging. 9. Context-Free Grammars for English. 10. Parsing with Context-Free Grammars. 11. Features and Unification. 12. Lexicalized and Probabilistsic Parsing. 13. Language and Complexity. III. SEMANTICS. 14. Representing Meaning. 15. Semantic Analysis. 16. Lexical Semantics. 17. Word Sense Disambiguation and Information Retrieval. IV. PRAGMATICS. 18. Discourse. 19. Dialogue and Conversational Agents. 20. Natural Language Generation. 21. Machine Translation. APPENDICES. A. Regular Expression Operators. B. The Porter Stemming Algorithm. C. C5 and C7 tagsets. D. Training HMMs: The Forward-Backward Algorithm. Bibliography. Index.
SynopsisThis book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing., For undergraduate or advanced undergraduate courses in Classical Natural Language Processing, Statistical Natural Language Processing, Speech Recognition, Computational Linguistics, and Human Language Processing. This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corporations. Author Website with Resources: http://www.cs.colorado.edu/~martin/slp.html
LC Classification NumberP98.J87 2000
