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Speech and Language Processing: An Introduction to Natural Language Processing,,
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Ubicado en: Multiple Locations, Estados Unidos
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Entrega prevista entre el vie. 26 sep. y el jue. 2 oct.
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N.º de artículo de eBay:166367021968
Última actualización el 30 jun 2025 18:32:11 H.EspVer todas las actualizacionesVer todas las actualizaciones
Características del artículo
- Estado
- En buen estado
- Notas del vendedor
- “Used book in good condition. Shows typical wear. Quick shipping. Satisfaction guaranteed!”
- Book Title
- Speech and Language Processing
- Narrative Type
- Software
- Genre
- N/A
- Intended Audience
- N/A
- ISBN
- 9780130950697
Acerca de este producto
Product Identifiers
Publisher
Pearson Education
ISBN-10
0130950696
ISBN-13
9780130950697
eBay Product ID (ePID)
1101471
Product Key Features
Number of Pages
934 Pages
Language
English
Publication Name
Speech and Language Processing : An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition
Publication Year
2000
Subject
Computer Vision & Pattern Recognition, Linguistics / General
Type
Textbook
Subject Area
Computers, Language Arts & Disciplines
Format
Hardcover
Dimensions
Item Height
1.5 in
Item Weight
52 Oz
Item Length
9.5 in
Item Width
7.3 in
Additional Product Features
Intended Audience
College Audience
LCCN
99-087845
Dewey Edition
22
Illustrated
Yes
Dewey Decimal
410.2/85
Table Of Content
1. 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.
Synopsis
This 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 Number
P98.J87 2000
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