Statistical Machine Translation [NOOK Book]

Overview

The dream of automatic language translation is now closer thanks to recent advances in the techniques that underpin statistical machine translation. This class-tested textbook from an active researcher in the field, provides a clear and careful introduction to the latest methods and explains how to build machine translation systems for any two languages. It introduces the subject's building blocks from linguistics and probability, then covers the major models for machine translation: word-based, phrase-based, and...
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Statistical Machine Translation

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Overview

The dream of automatic language translation is now closer thanks to recent advances in the techniques that underpin statistical machine translation. This class-tested textbook from an active researcher in the field, provides a clear and careful introduction to the latest methods and explains how to build machine translation systems for any two languages. It introduces the subject's building blocks from linguistics and probability, then covers the major models for machine translation: word-based, phrase-based, and tree-based, as well as machine translation evaluation, language modeling, discriminative training and advanced methods to integrate linguistic annotation. The book also reports the latest research, presents the major outstanding challenges, and enables novices as well as experienced researchers to make novel contributions to this exciting area. Ideal for students at undergraduate and graduate level, or for anyone interested in the latest developments in machine translation.
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Editorial Reviews

From the Publisher
"Philipp Koehn has provided the first comprehensive text for this rapidly growing field of statistical machine translation. This book is an invaluable resource for students, researcher, and software developers, providing a lucid and detailed presentation of all the important ideas needed to understand or create a state-of-the-art statistical machine translation system."
Robert C. Moore, Microsoft Research

"This is an excellent introduction for someone interested in statistical translation. It is quite readable..."
Jeffrey Putnam, Computing Reviews

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Product Details

  • ISBN-13: 9781139637565
  • Publisher: Cambridge University Press
  • Publication date: 12/5/2012
  • Sold by: Barnes & Noble
  • Format: eBook
  • Edition number: 1
  • File size: 12 MB
  • Note: This product may take a few minutes to download.

Meet the Author

Philipp Koehn is a lecturer in the School of Informatics at the University of Edinburgh. He is the scientific co-ordinator of the European EuroMatrix project and also involved in research funded by DARPA in the USA. He has also collaborated with leading companies in the field, such as Systran and Asia Online. He implemented the widely used decoder Pharoah, and is leading the development of the open source machine translation toolkit Moses.
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Table of Contents

1 Introduction 3

2 Words, Sentences, Corpora 33

3 Probability Theory 63

4 Word-Based Models 81

5 Phrase-Based Models 127

6 Decoding 155

7 Language Models 181

8 Evaluation 217

9 Discriminative Training 249

10 Integrating Linguistic Information 289

11 Tree-Based Models 331

Bibliography 371

Author Index 416

Index 427

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