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5th WORKSHOP ON BUILDING AND USING COMPARABLE CORPORA

Language Resources for Machine Translation
in Less-Resourced Languages and Domains

Co-located with LREC 2012
Lütfi Kirdar Istanbul Exhibition and Congress Centre
Saturday, 26 May 2012

DEADLINE FOR PAPERS: 15 February 2012

http://hnk.ffzg.hr/5bucc2012

Endorsed by
* ACL SIGWAC (Special Interest Group on Web as Corpus)
* FLaReNet (Fostering Language Resources Network)

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MOTIVATION

In the language engineering and the linguistics communities,
research in comparable corpora has been motivated by two main
reasons. In language engineering, it is chiefly motivated by the
need to use comparable corpora as training data for statistical
NLP applications such as statistical machine translation or
cross-lingual retrieval. In linguistics, on the other hand,
comparable corpora are of interest in themselves by making
possible inter-linguistic discoveries and comparisons. It is
generally accepted in both communities that comparable corpora
are documents in one or several languages that are comparable in
content and form in various degrees and dimensions. We believe
that the linguistic definitions and observations related to
comparable corpora can improve methods to mine such corpora for
applications of statistical NLP. As such, it is of great interest
to bring together builders and users of such corpora.

The scarcity of parallel corpora has motivated research concerning
the use of comparable corpora: pairs of monolingual corpora selected
according to the same set of criteria, but in different languages
or language varieties. Non-parallel yet comparable corpora overcome
the two limitations of parallel corpora, since sources for original,
monolingual texts are much more abundant than translated texts.
However, because of their nature, mining translations in comparable
corpora is much more challenging than in parallel corpora. What
constitutes a good comparable corpus, for a given task or per se,
also requires specific attention: while the definition of a parallel
corpus is fairly straightforward, building a non-parallel corpus
requires control over the selection of source texts in both languages.

Parallel corpora are a key resource as training data for statistical
machine translation, and for building or extending bilingual lexicons
and terminologies. However, beyond a few language pairs such as English-
French or English-Chinese and a few contexts such as parliamentary debates
or legal texts, they remain a scarce resource, despite the creation of
automated methods to collect parallel corpora from the Web. To exemplify
such issues in a practical setting, this year's special focus will be on

Language Resources for Machine Translation
in Less-Resourced Languages and Domains

with the aim of overcoming the shortage of parallel resources
when building MT systems for less-resourced languages and domains,
particularly by usage of comparable corpora for finding parallel data
within and by reaching out for "hidden" parallel data. Lack of sufficient
language resources for many language pairs and domains is currently one
of the major obstacles in further advancement of machine translation.


TOPICS

We solicit contributions including but not limited to the following topics:

Topics related to the special theme:

* comparable corpora use in MT
* comparable corpora processing tools/kits for MT
* parallel corpora usage
* parallel corpora processing tools/platforms
* MT for less-resourced languages
* MT for less-resourced domains
* open source SMT systems (Moses, etc.)
* publicly available SMT

Building Comparable Corpora:

* Human translations
* Automatic and semi-automatic methods
* Methods to mine parallel and non-parallel corpora from the Web
* Tools and criteria to evaluate the comparability of corpora
* Parallel vs non-parallel corpora, monolingual corpora
* Rare and minority languages
* Across language families
* Multi-media/multi-modal comparable corpora

Applications of comparable corpora:

* Human translations
* Language learning
* Cross-language information retrieval & document categorization
* Bilingual projections
* Machine translation
* Writing assistance

Mining from Comparable Corpora:

* Extraction of parallel segments or paraphrases from comparable
corpora
* Extraction of bilingual and multilingual translations of single
words and multi-word expressions; proper names, named entities,
etc.


IMPORTANT DATES (TENTATIVE)

15 February 2012 Deadline for submission of full papers
10 March 2012 Notification of acceptance
20 March 2012 Camera-ready papers due
26 May 2012 Workshop date


SUBMISSION INFORMATION

Papers should follow the LREC main conference formatting details (to be
announced on the conference website http://www.lrec-conf.org/lrec2012/)
and should be submitted as a PDF-file of no more than ten pages via the
START workshop manager: https://www.softconf.com/lrec2012/BUCC2012/
Reviewing will be double blind, so the papers should not reveal the
authors' identity. Accepted papers will be published in the workshop
proceedings.

Double submission policy: Parallel submission to other meetings or
publications are possible but must be immediately notified to the
workshop organizers.

When submitting a paper through the START page, authors will be asked
to provide information about the resources that have been used for the work
described in their paper or are an outcome of their research. For details on
this initiative, please refer to http://www.lrec-conf.org/lrec2012/?LRE-Map-2012.
Authors will also be asked to contribute to the Language Library, the new
initiative of LREC 2012.

For further information, please contact
Reinhard Rapp reinhardrapp (at) gmx (dot) de
or Marko Tadic marko.tadic (at) ffzg (dot) hr


ORGANISERS

Reinhard Rapp, Universities of Mainz (Germany)and Leeds (UK)
Marko Tadic, University of Zagreb (Croatia)
Serge Sharoff, University of Leeds (UK)
Andrejs Vasiljevs, Tilde SIA, Riga, Latvia
Pierre Zweigenbaum, LIMSI, CNRS, Orsay, and ERTIM, INALCO, Paris (France)


SCIENTIFIC COMMITTEE

* Srinivas Bangalore (AT&T Labs, USA)
* Caroline Barrière (National Research Council Canada)
* Chris Biemann (Microsoft / Powerset, San Francisco, USA)
* Lynne Bowker (University of Ottawa, Canada)
* Hervé Déjean (Xerox Research Centre Europe, Grenoble, France)
* Andreas Eisele (DFKI, Saarbrücken, Germany)
* Rob Gaizauskas (University of Sheffield, UK)
* Éric Gaussier (Université Joseph Fourier, Grenoble, France)
* Nikos Glaros (ILSP, Athens, Greece)
* Gregory Grefenstette (Exalead/Dassault Systemes, Paris, France)
* Silvia Hansen-Schirra (University of Mainz, Germany)
* Kyo Kageura (University of Tokyo, Japan)
* Adam Kilgarriff (Lexical Computing Ltd, UK)
* Natalie Kübler (Université Paris Diderot, France)
* Philippe Langlais (Université de Montréal, Canada)
* Tony McEnery (Lancaster University, UK)
* Emmanuel Morin (Université de Nantes, France)
* Dragos Stefan Munteanu (Language Weaver Inc., USA)
* Lene Offersgaard (University of Copenhagen, Denmark)
* Reinhard Rapp (Universities of Mainz, Germany, and Leeds, UK)
* Sujith Ravi (Yahoo! Research, Santa Clara, CA, USA)
* Serge Sharoff (University of Leeds, UK)
* Michel Simard (National Research Council Canada)
* Inguna Skadina (Tilde, Riga, Latvia)
* Monique Slodzian (INALCO, Paris, France)
* Benjamin Tsou (The Hong Kong Institute of Education, China)
* Dan Tufis (Romanian Academy, Bucharest, Romania)
* Justin Washtell (University of Leeds, UK)
* Oliver Wilson (University of Edinburgh, UK)
* Michael Zock (LIF, CNRS Marseille, France)
* Pierre Zweigenbaum (LIMSI-CNRS, Orsay, France)