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Analysis and Evaluation of Comparable Corpora for Under-Resourced Areas of Machine Translation

Analysis and Evaluation of Comparable Corpora for Under-Resourced Areas of Machine Translation

  • Duration:

The project aims at researching methods and techniques to overcome one of the central problems of machine translation (MT) – the lack of linguistic resources such as training data for under-resourced areas of machine translation. The main goal is to find, analyze and evaluate novel methods that exploit comparable corpora on order to compensate for the shortage of linguistic resources, and ultimately to significantly improve MT quality for under-resourced languages and narrow domains. Models generated from comparable corpora will be compared against baseline models generated from parallel corpora.

Partners

  • Tilde, LV (Coordinator)
  • University of Sheffield, UK
  • University of Leeds, School of Modern Languages and Cultures, Centre for Translation Studies, UK
  • Institute for Language and Speech Processing, GR
  • University of Zagreb, HR
  • German Research Center for Artificial Intelligence, Language Technology Lab, DE
  • Research Institute for AI, Romanian Academy, Romania
  • Linguatec, Germany
  • Zemanta, Slovenia

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Publications about the project

Sabine Hunsicker, Radu Ion, Dan Stefanescu

In: Proceedings of the 16th Annual Conference of the European Association for Machine Translation. Annual Conference of the European Association for Machine Translation (EAMT-12) May 28-30 Trento Italy 2012.

To the publication
Jia Xu, Weiwei Sun

In: MT Summit XIII. Machine Translation Summit (MT-Summit-11) 13. September 19-23 Xiaman China NA Xiamen 9/2011.

To the publication
Kaveh Taghipour, Shahram Khadivi, Jia Xu

In: MT Summit XIII. Machine Translation Summit (MT-Summit-11) 13. September 19-23 Xiamen China NA Xiamen 9/2011.

To the publication

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz