DFKI-LT - Improving Machine Translation Performance Using Comparable Corpora

Andreas Eisele, Jia Xu
Improving Machine Translation Performance Using Comparable Corpora
in: Serge Sharoff Pierre Zweigenbaum Reinhard Rapp (ed.):
2 Proceedings of the 3rd Workshop on Building and Using Comparable Corpora, Pages 35-41, La Valletta, Malta, European Language Resources Association (ELRA), 5/2010
The overwhelming majority of the languages in the world are spoken by less than 50 million native speakers, and automatic translation of many of these languages is less investigated due to the lack of linguistic resources such as parallel corpora. In the ACCURAT project we will work on novel methods how comparable corpora can compensate for this shortage and improve machine translation systems of under-resourced languages. Translation systems on eighteen European language pairs will be investigated and methodologies in corpus linguistics will be greatly advanced. We will explore the use of preliminary SMT models to identify the parallel parts within comparable corpora, which will allow us to derive better SMT models via a bootstrapping loop.
Files: BibTeX, accuratfinal.pdf