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Foundations of Text Alignment: Statistical Machine Translation Models from Bitexts to Bigrammars (Theory and Applications of Natural Language Processing)

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Foundations of Text Alignment: Statistical Machine Translation Models from Bitexts to Bigrammars (Theory and Applications of Natural Language Processing) Cover

 

Synopses & Reviews

Publisher Comments:

This book provides a systematic, foundational introduction to automatic alignment of parallel texts, a family of essential corpus analysis techniques for computing and learning the mappings between corresponding parts of the texts. Bitext alignment lies at the heart of all data-driven machine learning approaches to automatic translation, and the rapid research progress on alignment during the past two decades underlies the success of statistical machine translation approaches.

Synopsis:

Bi-text alignment lies at the heart of all data-driven machine-learning approaches to automatic translation and is an essential technique of analysis. This book provides a systematic, foundational introduction to the automatic alignment of parallel texts.

About the Author

Prof. Wu received his PhD in Computer Science from the University of California at Berkeley, and was a postdoctoral fellow at the University of Toronto (Ontario, Canada) prior to joining HKUST in 1992. He received his Executive MBA from Kellogg and HKUST in 2002, and a BS in Computer Engineering from the University of California at San Diego (Revelle College departmental award, cum laude, Phi Beta Kappa) in 1984. He has been a visiting researcher at Columbia University in 1995-96, Bell Laboratories in 1995, and the Technische Universität München (Munich, Germany) during 1986-87. Prof. Wu serves as Associate Editor of AI Journal and on the Editorial Board of Machine Translation and Journal of Natural Language Engineering. He has also served as Co-Chair for EMNLP-2004, and on the Editorial Board of Computational Linguistics and as Associate Editor of ACM Transactions on Speech and Language Processing, the Organizing Committee of ACL-2000 and WVLC-5 (SIGDAT 1997), and the Executive Committee of the Association for Computational Linguistics (ACL).

Product Details

ISBN:
9783642258435
Author:
Wu, Dekai
Publisher:
Springer
Location:
Berlin, Heidelberg
Subject:
Applied
Subject:
bilingual lexicography
Subject:
computer assisted language learning
Subject:
grammar induction
Subject:
Machine learning
Subject:
statistical machine translation
Subject:
terminology extraction
Subject:
Word Sense Disambiguation
Subject:
APPLICATIONS OF MATHEMATICS
Subject:
Language Translation and Linguistics
Subject:
Probability and Statistics in Computer Science
Subject:
Computer Science, general
Subject:
Mathematics-Applied
Subject:
Mathematics
Subject:
The Arts
Subject:
Humanities, Social Sciences and Law
Subject:
Translators (Computer programs)
Subject:
Computer Science
Copyright:
Edition Description:
2012
Series:
Theory and Applications of Natural Language Processing
Publication Date:
20120126
Binding:
HARDCOVER
Language:
English
Pages:
100
Dimensions:
235 x 155 mm

Related Subjects

Computers and Internet » Computers Reference » General
Computers and Internet » Personal Computers » General
Computers and Internet » Software Engineering » Programming and Languages
Health and Self-Help » Psychology » General
Science and Mathematics » Mathematics » Applied

Foundations of Text Alignment: Statistical Machine Translation Models from Bitexts to Bigrammars (Theory and Applications of Natural Language Processing) New Hardcover
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Product details 100 pages Springer - English 9783642258435 Reviews:
"Synopsis" by , Bi-text alignment lies at the heart of all data-driven machine-learning approaches to automatic translation and is an essential technique of analysis. This book provides a systematic, foundational introduction to the automatic alignment of parallel texts.
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