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Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition, 2/e

Speech and Language Processing:  An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition,  2/e

Author(s):
  • Daniel Jurafsky
  • Author: Daniel Jurafsky
    • ISBN:9789332518414
    • 10 Digit ISBN:9332518416
    • Price:Rs. 1099.00
    • Pages:940
    • Imprint:Pearson Education
    • Binding:Paperback
    • Status:Available


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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 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.

    Table of Content

    Contents 1. Introduction
    Part I Words
    2. Regular Expressions and Automata
    3. Words and Transducers
    4. N-grams
    5. Part-of-Speech Tagging
    6. Hidden Markov and Maximum Entropy Models
    Part II Speech
    7. Phonetics
    8. Speech Synthesis
    9. Automatic Speech Recognition
    10. Speech Recognition: Advanced Topics
    11. Computational Phonology
    Part III Syntax
    12. Formal Grammars of English
    13. Syntactic Parsing
    14. Statistical Parsing
    15. Features and Unification
    16. Language and Complexity
    Part IV Semantics and Pragmatics
    17. The Representation of Meaning
    18. Computational Semantics
    19. Lexical Semantics
    20. Computational Lexical Semantics
    21. Computational Discourse
    Part V Applications
    22. Information Extraction
    23. Question Answering and Summarization
    24. Dialogue and Conversational Agents
    25. Machine Translation

     

    Salient Features

    • Each chapter is built around one or more worked examples demonstrating the main idea of the chapter - Uses the examples to illustrate the relative strengths and weaknesses of various approaches
    • Methodology boxes included in each chapter - Introduces important methodological tools such as evaluation, wizard of oz techniques, etc.
    • 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.
    • 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.
    • Emphasis on Web and other practical applications - Gives students an understanding of how language-related algorithms can be applied to important real-world problems.
    • Emphasis on scientific evaluation - Offers a description of how systems are evaluated with each problem domain.
    • Description of widely available language processing resources
    • Seven new chapters that extend coverage to include:
    o Statistical sequence labeling
    o Information extraction
    o Question answering and summarization
    o Advanced topics in speech recognition
    o Speech synthesis