Statistical Machine Translation

Philipp Koehn

doi:10.1017/CBO9780511815829

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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.

'Philipp Koehn has provided the first comprehensive text for the rapidly growing field of statistical machine translation. This book is an invaluable resource for students, researchers, 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 - Principal Researcher, Microsoft Research

'The book primarily represents an ideal introduction to the field of statistical machine translation, but also tackles many of the recent results in this area. It is the product of the many years of both active research and extensive teaching of the author … Each chapter is additionally endowed with a summary, further reading and exercises, achieving thus completely the proposed goal of an accessible introduction to the statistical machine translation field. Apart from its formative role for beginners, the book also stands as a complete guide for researchers in a domain of high interest and rapid expansion … For all these reasons, this book should be welcomed as a highly valuable publication.'

Source: Zentralblatt MATH

'… Statistical Machine Translation provides an excellent synthesis of a vast amount of literature (the bibliography section takes up 45 double-column pages) and presents it in a well-structured and articulate way. Moreover, the book has been class-tested and contains a set of exercises at the end of each chapter, as well as numerous references to open source tools and resources which enable the diligent reader to build MT systems for any language pair.'

Source: Target: International Journal of Translation Studies

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Contents

Frontmatter
pp i-vi
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Contents
pp vii-x
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Preface
pp xi-xii
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I - Foundations
pp 1-2
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1 - Introduction
pp 3-32
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2 - Words, Sentences, Corpora
pp 33-62
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3 - Probability Theory
pp 63-78
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II - Core Methods
pp 79-80
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4 - Word-Based Models
pp 81-126
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5 - Phrase-Based Models
pp 127-154
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6 - Decoding
pp 155-180
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7 - Language Models
pp 181-216
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8 - Evaluation
pp 217-246
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III - Advanced Topics
pp 247-248
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9 - Discriminative Training
pp 249-288
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10 - Integrating Linguistic Information
pp 289-330
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11 - Tree-Based Models
pp 331-370
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Bibliography
pp 371-415
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Author Index
pp 416-426
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Index
pp 427-433
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Statistical Machine Translation

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Contents

Frontmatter
pp i-vi

Contents
pp vii-x

Preface
pp xi-xii

I - Foundations
pp 1-2

1 - Introduction
pp 3-32

2 - Words, Sentences, Corpora
pp 33-62

3 - Probability Theory
pp 63-78

II - Core Methods
pp 79-80

4 - Word-Based Models
pp 81-126

5 - Phrase-Based Models
pp 127-154

6 - Decoding
pp 155-180

7 - Language Models
pp 181-216

8 - Evaluation
pp 217-246

III - Advanced Topics
pp 247-248

9 - Discriminative Training
pp 249-288

10 - Integrating Linguistic Information
pp 289-330

11 - Tree-Based Models
pp 331-370

Bibliography
pp 371-415

Author Index
pp 416-426

Index
pp 427-433

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Accessibility standard: Unknown

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Statistical Machine Translation

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