Syntax-based Statistical Machine Translation

Philip Williams, Rico Sennrich, Matt Post and Philipp Koehn

ISBN 10: 1627059008 ISBN 13: 9781627059008

Published by Morgan & Claypool, [Kentfield CA], 2016

Language: English

Condition: New Soft cover

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A digital text - this copy printed in the UK. Quarto-size, 212 pages (xvii, 194), diagrams, charts &c, bibliography, index; publisher's pictorial card covers: New and unread. Pictures show this actual book.

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Bibliographic Details

Title

Syntax-based Statistical Machine Translation

Publisher

Morgan & Claypool, [Kentfield CA]

Publication Date

2016

Language

English

ISBN 10

1627059008

ISBN 13

9781627059008

Binding

Softcover/Paperback

Edition

First Edition.

Printing

First printing

Condition

New

Dust Jacket Condition

No Jacket

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Synopsis

This unique book provides a comprehensive introduction to the most popular syntax-based statistical machine translation models, filling a gap in the current literature for researchers and developers in human language technologies. While phrase-based models have previously dominated the field, syntax-based approaches have proved a popular alternative, as they elegantly solve many of the shortcomings of phrase-based models. The heart of this book is a detailed introduction to decoding for syntax-based models.

The book begins with an overview of synchronous-context free grammar (SCFG) and synchronous tree-substitution grammar (STSG) along with their associated statistical models. It also describes how three popular instantiations (Hiero, SAMT, and GHKM) are learned from parallel corpora. It introduces and details hypergraphs and associated general algorithms, as well as algorithms for decoding with both tree and string input. Special attention is given to efficiency, including search approximations such as beam search and cube pruning, data structures, and parsing algorithms. The book consistently highlights the strengths (and limitations) of syntax-based approaches, including their ability to generalize phrase-based translation units, their modeling of specific linguistic phenomena, and their function of structuring the search space.

About the Author

University of Edinburgh|Heidelberg University, Germany|Johns Hopkins University|Johns Hopkins University

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