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Speech and Language Processing, 2nd edition

  • Daniel Jurafsky
  • James H. Martin

Published by Pearson (May 16th 2008) - Copyright © 2009

2nd edition

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Speech and Language Processing

ISBN-13: 9780131873216

Includes: Hardcover
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$159.99 $199.99

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  • Hardcover

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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 book takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. KEY TOPICS: Builds each chapter around one or more worked examples demonstrating the main idea of the chapter, usingthe examples to illustrate the relative strengths and weaknesses of various approaches. Adds coverage of statistical sequence labeling, information extraction, question answering and summarization, advanced topics in speech recognition, speech synthesis. Revises coverage of language modeling, formal grammars, statistical parsing, machine translation, and dialog processing. MARKET: A useful reference for professionals in any of the areas of speech and language processing.

Table of contents



About the Authors 


1 Introduction

1.1 Knowledge in Speech and Language Processing

1.2 Ambiguity

1.3 Models and Algorithms

1.4 Language, Thought, and Understanding

1.5 The State of the Art

1.6 Some Brief History

1.6.1 Foundational Insights: 1940s and 1950s

1.6.2 The Two Camps: 1957—1970

1.6.3 Four Paradigms: 1970—1983

1.6.4 Empiricism and Finite State Models Redux: 1983—1993

1.6.5 The Field Comes Together: 1994—1999

1.6.6 The Rise of Machine Learning: 2000—2008

1.6.7 On Multiple Discoveries

1.6.8 A Final Brief Note on Psychology

1.7 Summary

Bibliographical and Historical Notes


Part I Words


2 Regular Expressions and Automata

2.1 Regular Expressions

2.1.1 Basic Regular Expression Patterns

2.1.2 Disjunction, Grouping, and Precedence

2.1.3 A Simple Example

2.1.4 A More Complex Example

2.1.5 Advanced Operators

2.1.6 Regular Expression Substitution, Memory, and ELIZA

2.2 Finite-State Automata

2.2.1 Using an FSA to Recognize Sheeptalk

2.2.2 Formal Languages

2.2.3 Another Example

2.2.4 Non-Deterministic FSAs

2.2.5 Using an NFSA to Accept Strings

2.2.6 Recognition as Search

2.2.7 Relating Deterministic and Non-Deterministic Automata

2.3 Regular Languages and FSAs

2.4 Summary

Bibliographical and Historical Notes



3 Words and Transducers

3.1 Survey of (Mostly) English Morphology

3.1.1 Inflectional Morphology

3.1.2 Derivational Morphology

3.1.3 Cliticization

3.1.4 Non-Concatenative Morphology

3.1.5 Agreement

3.2 Finite-State Morphological Parsing

3.3 Construction of a Finite-State Lexicon

3.4 Finite-State Transducers

3.4.1 Sequential Transducers and Determinism

3.5 FSTs for Morphological Parsing

3.6 Transducers and Orthographic Rules

3.7 The COmbination of an FST Lexicon and Rules

3.8 Lexicon-Free FSTs: The Porter Stemmer

3.9 Word and Sentence Tokenization

3.9.1 Segmentation in Chinese

3.10 Detection and Correction of Spelling Errors

3.11 Minimum Edit Distance

3.12 Human Morphological Processing

3.13 Summary


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