Livre: Learning Machine Translation

[Thierry Hamon]

Date: Thu, 29 Jan 2009 18:09:31 +0100
From: "Dymetman, Marc" <Marc.Dymetman at xrce.xerox.com>
Message-ID: <FE4C3A2704112F4B8FCD916BBDDA33E706C0454F at luberon.xrce.xeroxlabs.com>
X-url: http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=11753
X-url: http://www.amazon.com/Learning-Machine-Translation-Information-Processing/dp/0262072971/ref=sr_1_1?ie=UTF8&s=books&qid=1233175113&sr=8-1

Dear colleagues,

We would like to announce the publication of a new book, which should
be relevant to people interested in the use of Machine Learning
techniques for Statistical Machine Translation.

 
Learning Machine Translation

C. Goutte, N. Cancedda, M. Dymetman and G. Foster (eds)

Series: Neural Information Processing

ISBN-13: 978-0-262-07297-7

http://mitpress.mit.edu/catalog/item/default.asp?ttype=2&tid=11753

http://www.amazon.com/Learning-Machine-Translation-Information-Processing/dp/0262072971/ref=sr_1_1?ie=UTF8&s=books&qid=1233175113&sr=8-1 

The Internet gives us access to a wealth of information in languages
we don't understand. The investigation of automated or semi-automated
approaches to translation has become a thriving research field with
enormous commercial potential. This volume investigates how machine
learning techniques can improve statistical machine translation,
currently at the forefront of research in the field.

The book looks first at enabling technologies: technologies that solve
problems that are not machine translation proper but are linked
closely to the development of a machine translation system. These
include the acquisition of bilingual sentence-aligned data from
comparable corpora, automatic construction of multilingual name
dictionaries, and word alignment. The book then presents new or
improved statistical machine translation techniques, including a
discriminative training framework for leveraging syntactic
information, the use of semi-supervised and kernel-based learning
methods, and the combination of multiple machine translation outputs
in order to improve overall translation quality.

Contributors: Srinivas Bangalore, Nicola Cancedda, Josep M. Crego,
Marc Dymetman, Jakob Elming, George Foster, Jesús Giménez, Cyril
Goutte, Nizar Habash, Gholamreza Haffari, Patrick Haffner, Hitoshi
Isahara, Stephan Kanthak, Alexandre Klementiev, Gregor Leusch, Pierre
Mahé, Lluís Màrquez, Evgeny Matusov, I. Dan Melamed, Ion Muslea,
Hermann Ney, Bruno Pouliquen, Dan Roth, Anoop Sarkar, John
Shawe-Taylor, Ralf Steinberger, Joseph Turian, Nicola Ueffing, Masao
Utiyama, Zhuoran Wang, Benjamin Wellington, Kenji Yamada

Neural Information Processing series

About the Editors

Cyril Goutte is a researcher in the Interactive Language Technologies
Group at the Canadian National Research Council's Institute for
Information Technology.

Nicola Cancedda is a researcher in the Cross-Language Technologies
Research Group at the Xerox Research Centre Europe.

Marc Dymetman is a researcher in the Cross-Language Technologies
Research Group at the Xerox Research Centre Europe.

George Foster is a researcher in the Interactive Language Technologies
Group at the Canadian National Research Council's Institute for
Information Technology.

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