International Workshop on Spoken Language Translation (IWSLT) 2009

Tokyo, Japan
December 1-2, 2009

Low-Resource Machine Translation Using MATREX: The DCU Machine Translation System for IWSLT 2009

Yanjun Ma, Tsuyoshi Okita, Özlem Çetinoğlu, Jinhua Du, Andy Way

Centre for Next Generation Localisation, School of Computing, Dublin City University, Dublin, Ireland

In this paper, we give a description of the Machine Translation (MT) system developed at DCU that was used for our fourth participation in the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT 2009). Two techniques are deployed in our system in order to improve the translation quality in a low-resource scenario. The first technique is to use multiple segmentations in MT training and to utilise word lattices in decoding stage. The second technique is used to select the optimal training data that can be used to build MT systems. In this year's participation, we use three different prototype SMT systems, and the output from each system are combined using standard system combination method. Our system is the top system for Chinese–English CHALLENGE task in terms of BLEU score.

Full Paper     Presentation (pdf)

Bibliographic reference.  Ma, Yanjun / Okita, Tsuyoshi / Çetinoğlu, Özlem / Du, Jinhua / Way, Andy (2009): "Low-resource machine translation using MATREX: the DCU machine translation system for IWSLT 2009", In IWSLT-2009, 29-36.