Speech and Language Processing: Pearson New International Edition
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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.
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- Pearson International Content
- 9781292037936
- 9781292025438
- Page Fidelity (PDF)
- 2
- Daniel Jurafsky; James H. Martin
- English
- 2013-08-29
- 100
- 2
- 2
Kaflar
- Table of Contents
- Chapter 1. Introduction
- Chapter 2. Regular Expressions and Automata
- Chapter 3. Words and Transducers
- Chapter 4. N-Grams
- Chapter 5. Part-of-Speech Tagging
- Chapter 6. Hidden Markov and Maximum Entropy Models
- Chapter 7. Phonetics
- Chapter 8. Speech Synthesis
- Chapter 9. Automatic Speech Recognition
- Chapter 10. Speech Recognition: Advanced Topics
- Chapter 11. Computational Phonology
- Chapter 12. Formal Grammars of English
- Chapter 13. Syntactic Parsing
- Chapter 14. Statistical Parsing
- Chapter 15. Features and Unification
- Chapter 16. Language and Complexity
- Chapter 17. The Representation of Meaning
- Chapter 18. Computational Semantics
- Chapter 19. Lexical Semantics
- Chapter 20. Computational Lexical Semantics
- Chapter 21. Computational Discourse
- Chapter 22. Information Extraction
- Chapter 23. Question Answering and Summarization
- Chapter 24. Dialogue and Conversational Agents
- Chapter 25. Machine Translation
- Index
- A
- B
- C
- D
- E
- F
- G
- H
- I
- J
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
- X
- Y
- Z