Theory and Applications of Natural Language Processing

Coarse-to-Fine Natural Language Processing

Authors: Petrov, Slav

  • Foreword written by Eugene Charniak
  • This book describes a particular approach to natural language processing and its applications to several tasks  
  • Many applications are presented
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About this book

The impact of computer systems that can understand natural language will be tremendous. To develop this capability we need to be able to automatically and efficiently analyze large amounts of text. Manually devised rules are not sufficient to provide coverage to handle the complex structure of natural language, necessitating systems that can automatically learn from examples. To handle the flexibility of natural language, it has become standard practice to use statistical models, which assign probabilities for example to the different meanings of a word or the plausibility of grammatical constructions.

This book develops a general coarse-to-fine framework for learning and inference in large statistical models for natural language processing.

Coarse-to-fine approaches exploit a sequence of models which introduce complexity gradually. At the top of the sequence is a trivial model in which learning and inference are both cheap. Each subsequent model refines the previous one, until a final, full-complexity model is reached. Applications of this framework to syntactic parsing, speech recognition and machine translation are presented, demonstrating the effectiveness of the approach in terms of accuracy and speed. The book is intended for students and researchers interested in statistical approaches to Natural Language Processing.

Slav’s work Coarse-to-Fine Natural Language Processing represents a major advance in the area of syntactic parsing, and a great advertisement for the superiority of the machine-learning approach.

Eugene Charniak (Brown University)

About the authors

Slav Petrov is a Research Scientist at Google New York. He works on problems at the intersection of natural language processing and machine learning. In particular, he is interested in syntactic parsing and its applications to machine translation and information extraction. He also teaches Statistical Natural Language Processing at New York University as an Adjunct Professor.

Table of contents (6 chapters)

  • Introduction

    Petrov, Slav

    Pages 1-6

  • Latent Variable Grammars for Natural Language Parsing

    Petrov, Slav

    Pages 7-46

  • Discriminative Latent Variable Grammars

    Petrov, Slav

    Pages 47-67

  • Structured Acoustic Models for Speech Recognition

    Petrov, Slav

    Pages 69-82

  • Coarse-to-Fine Machine Translation Decoding

    Petrov, Slav

    Pages 83-98

Buy this book

eBook $149.00
price for USA
  • ISBN 978-3-642-22743-1
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $189.00
price for USA
  • ISBN 978-3-642-22742-4
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $189.00
price for USA
  • ISBN 978-3-642-42749-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Coarse-to-Fine Natural Language Processing
Authors
Series Title
Theory and Applications of Natural Language Processing
Copyright
2012
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-642-22743-1
DOI
10.1007/978-3-642-22743-1
Hardcover ISBN
978-3-642-22742-4
Softcover ISBN
978-3-642-42749-7
Series ISSN
2192-032X
Edition Number
1
Number of Pages
XXII, 106
Topics