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Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition
Daniel Jurafsky, University of Colorado, Boulder
James H. Martin, University of Colorado, Boulder

ISBN-10: 0130950696
ISBN-13: 9780130950697

Publisher: Prentice Hall
Copyright: 2000
Format: Paper; 934 pp
Published: 01/26/2000

This item has been replaced by Speech and Language Processing, 2/E.

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

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. Ex.___

Methodology boxes—Included in each chapter.
- Introduces important methodological tools such as evaluation, wizard of oz techniques, etc. Ex.___

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. Ex.___

Emphasis on Web and other practical applications.
- Gives students an understanding of how language-related algorithms can be applied to important real-world problems. Ex.___

Emphasis on scientific evaluation—Offers a description of how systems are evaluated with each problem domain.

Description of widely available language processing resources.

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.

Natural Language Processing (Computer Science)
Speech Processing [CORE TEXTS] (Electrical and Computing Engineering)

Speech and Language Processing, 2/E
Jurafsky & Martin
©2009 | Prentice Hall | Cloth; 1024 pp | Instock
ISBN-10: 0131873210 | ISBN-13: 9780131873216
Brief Description | Buy from myPearsonStore
For undergraduate or advanced undergraduate courses in Classical Natural Language Processing, Statistical Natural Language Processing, Speech Recognition, Computational Linguistics, and Human Language Processing.

An explosion of Web-based language techniques, merging of distinct fields, availability of phone-based dialogue systems, and much more make this an exciting time in speech and language processing. The first of its kind to thoroughly cover language technology — at all levels and with all modern technologies — this text takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. The authors cover areas that traditionally are taught in different courses, to describe a unified vision of speech and language processing. Emphasis is on practical applications and scientific evaluation. An accompanying Website contains teaching materials for instructors, with pointers to language processing resources on the Web. The Second Edition offers a significant amount of new and extended material.

Supplements:

Click on the "Resources" tab to View Downloadable Files:

Solutions

Power Point Lecture Slides - Chapters 1-5, 8-10, 12-13 and 24 Now Available!

For additional resourcse visit the author website: http://www.cs.colorado.edu/~martin/slp.html

Companion Website-Jurafsky
Jurafsky
©2000 | Prentice Hall | On-line Supplement | Instock
ISBN-10: 013026959X | ISBN-13: 9780130269591
URL: http://www.cs.colorado.edu/~martin/slp.html

Interwrite Personal Response System
EduCue, Addison-Wesley & Benjamin Cummings
©2004 | Prentice Hall | Electronic Supplement | Instock
ISBN-10: 0321267354 | ISBN-13: 9780321267351

Companion Website-Jurafsky
Jurafsky
©2000 | Prentice Hall | On-line Supplement | Instock
ISBN-10: 013026959X | ISBN-13: 9780130269591
URL: http://www.cs.colorado.edu/~martin/slp.html

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