8th Workshop on Building and Using Comparable Corpora

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 intra-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.

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. Interest in non-parallel forms of comparable corpora in language engineering primarily ensued from the scarcity of parallel corpora. This 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.

Research on comparable corpora spans a number of topics from machine translation to contrastive linguistics. Distributional analysis, a topic which has seen renewed interest in recent years, has formed the core of a large part of the methods used to identify translations in comparable corpora. As a matter of fact, the standard techniques of word alignment in comparable corpora can be seen as methods for cross-language distributional semantics.

Previous BUCC Workshops

IssueVenue ChairpersonsProceedings
BUCC 2008LREC, Marrakech Pierre Zweigenbaum, Éric Gaussier, Pascale Fung PDF
BUCC 2009ACL, Singapore Pascale Fung, Pierre Zweigenbaum, Reinhard Rapp PDF [Individual papers]
BUCC 2010LREC, Valetta Reinhard Rapp, Pierre Zweigenbaum, Serge Sharoff PDF
BUCC 2011ACL, Portland Pierre Zweigenbaum, Reinhard Rapp, Serge Sharoff PDF [Individual papers]
BUCC 2012LREC, Istanbul Reinhard Rapp, Marko Tadić, Serge Sharoff, Andrejs Vasiļjevs, Pierre Zweigenbaum PDF
BUCC 2013ACL, Sofia Serge Sharoff, Pierre Zweigenbaum, Reinhard Rapp PDF [Individual papers]
BUCC 2014LREC, Reykjavik Pierre Zweigenbaum, Ahmet Aker, Serge Sharoff, Stephan Vogel, Reinhard Rapp PDF