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ISCApad Archive  »  2014  »  ISCApad #187  »  Events  »  Other Events  »  (2014-05-27) 7th WORKSHOP ON BUILDING AND USING COMPARABLE CORPORA, Reykjavik (Iceland)

ISCApad #187

Saturday, January 11, 2014 by Chris Wellekens

3-3-36 (2014-05-27) 7th WORKSHOP ON BUILDING AND USING COMPARABLE CORPORA, Reykjavik (Iceland)
1st Call for Papers

  Building Resources for Machine Translation Research
  May 27, 2014
  Co-located with LREC 2014
  Harpa Conference Centre, Reykjavik (Iceland)
  DEADLINE FOR PAPERS: February 10, 2014
In the language engineering and the linguistics communities, research
in comparable corpora has been motivated by two main reasons. In
language engineering, on the one hand, it is chiefly motivated by the
need to use comparable corpora as training data for statistical
Natural Language Processing 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
    Building Resources for Machine Translation Research
This special topic aims to address the need for:
(1) Machine Translation training and testing data such as spoken or
written monolingual, comparable or parallel data collections, and
(2) methods and tools used for collecting, annotating, and verifying
MT data such as Web crawling, crowdsourcing, tools for language
experts and for finding MT data in comparable corpora.

We solicit contributions including but not limited to the following topics:
Topics related to the special theme:
  * Methods and tools for collecting and processing MT data,
        including crowdsourcing
  * Methods and tools for quality control
  * Tools for efficient annotation
  * Bilingual term and named entity collections
  * Multilingual treebanks, wordnets, propbanks, etc.
  * Comparable corpora with parallel units annotated
  * Comparable corpora for under-resourced languages and specific domains
  * Multilingual corpora with rich annotations:
        POS tags, NEs, dependencies, semantic roles, etc.
  * Data for special applications: patent translation, movie
        subtitles, MOOCs, meetings, chat-rooms, social media, etc.
  * Legal issues with collecting and redistributing data
        and generating derivatives
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.

  February 10, 2014    Deadline for submission of full papers
      March 10, 2014    Notification of acceptance
      March 27, 2014    Camera-ready papers due
         May 27, 2014    Workshop date
Papers should follow the LREC main conference formatting details (to be
announced on the conference website )
and should be submitted as a PDF-file via the START workshop manager at
Contributions can be short or long papers. Short paper submission must
describe original and unpublished work without exceeding six (6)
pages. Characteristics of short papers include: a small, focused
contribution; work in progress; a negative result; an opinion piece;
an interesting application nugget. Long paper submissions must
describe substantial, original, completed and unpublished work without
exceeding ten (10) pages.
Reviewing will be double blind, so the papers should not reveal the
authors' identity. Accepted papers will be published in the workshop
Double submission policy: Parallel submission to other meetings or
publications is possible but must be immediately notified to the
workshop organizers.
When submitting a paper from the START page, authors will be asked to
provide essential information about resources (in a broad sense,
i.e. also technologies, standards, evaluation kits, etc.) that have
been used for the work described in the paper or are a new result of
your research.  Moreover, ELRA encourages all LREC authors to share
the described LRs (data, tools, services, etc.), to enable their
reuse, replicability of experiments, including evaluation ones, etc.
For further information, please contact
    Pierre Zweigenbaum pz (at) limsi (dot) fr

  Pierre Zweigenbaum, LIMSI, CNRS, Orsay (France)
  Ahmet Aker, University of Sheffield (UK)
  Serge Sharoff, University of Leeds (UK)
  Stephan Vogel, QCRI (Qatar)
  Reinhard Rapp, Universities of Mainz (Germany) and Aix-Marseille (France)

  * Ahmet Aker, University of Sheffield (UK)
  * Srinivas Bangalore (AT&T Labs, US)
  * Caroline Barrière (CRIM, Montréal, Canada)
  * Chris Biemann (TU Darmstadt, Germany)
  * Hervé Déjean (Xerox Research Centre Europe, Grenoble, France)
  * Kurt Eberle (Lingenio, Heidelberg, Germany)
  * Andreas Eisele (European Commission, Luxembourg)
  * Éric Gaussier (Université Joseph Fourier, Grenoble, France)
  * Gregory Grefenstette (INRIA, Saclay, France)
  * Silvia Hansen-Schirra (University of Mainz, Germany)
  * Hitoshi Isahara (Toyohashi University of Technology)
  * Kyo Kageura (University of Tokyo, Japan)
  * Adam Kilgarriff (Lexical Computing Ltd, UK)
  * Natalie Kübler (Université Paris Diderot, France)
  * Philippe Langlais (Université de Montréal, Canada)
  * Michael Mohler (Language Computer Corp., US)
  * Emmanuel Morin (Université de Nantes, France)
  * Dragos Stefan Munteanu (Language Weaver, Inc., US)
  * Lene Offersgaard (University of Copenhagen, Denmark)
  * Ted Pedersen (University of Minnesota, Duluth, US)
  * Reinhard Rapp (Université Aix-Marseille, France)
  * Sujith Ravi (Google, US)
  * Serge Sharoff (University of Leeds, UK)
  * Michel Simard (National Research Council Canada)
  * Richard Sproat (OGI School of Science & Technology, US)
  * Tim Van de Cruys (IRIT-CNRS, Toulouse, France)
  * Stephan Vogel, QCRI (Qatar)
  * Guillaume Wisniewski (Université Paris Sud & LIMSI-CNRS, Orsay, France)
  * Pierre Zweigenbaum (LIMSI-CNRS, Orsay, France)

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