The University of Maryland statistical machine translation system for the Fourth Workshop on Machine Translation (2009)
| Venue: | In Proceedings of the EACL-2009 Workshop on Statistical Machine Translation |
| Citations: | 6 - 3 self |
BibTeX
@INPROCEEDINGS{Dyer09theuniversity,
author = {Chris Dyer and Hendra Setiawan and Yuval Marton and Philip Resnik},
title = {The University of Maryland statistical machine translation system for the Fourth Workshop on Machine Translation},
booktitle = {In Proceedings of the EACL-2009 Workshop on Statistical Machine Translation},
year = {2009}
}
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Abstract
This paper describes the techniques we explored to improve the translation of news text in the German-English and Hungarian-English tracks of the WMT09 shared translation task. Beginning with a convention hierarchical phrase-based system, we found benefits for using word segmentation lattices as input, explicit generation of beginning and end of sentence markers, minimum Bayes risk decoding, and incorporation of a feature scoring the alignment of function words in the hypothesized translation. We also explored the use of monolingual paraphrases to improve coverage, as well as co-training to improve the quality of the segmentation lattices used, but these did not lead to improvements. 1
