Effective use of linguistic and contextual information for statistical machine translation (2008)
| Venue: | In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing |
| Citations: | 8 - 1 self |
BibTeX
@INPROCEEDINGS{Shen08effectiveuse,
author = {Libin Shen and Jinxi Xu and Bing Zhang and Spyros Matsoukas and Ralph Weischedel},
title = {Effective use of linguistic and contextual information for statistical machine translation},
booktitle = {In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing},
year = {2008},
pages = {72--80}
}
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Abstract
Current methods of using lexical features in machine translation have difficulty in scaling up to realistic MT tasks due to a prohibitively large number of parameters involved. In this paper, we propose methods of using new linguistic and contextual features that do not suffer from this problem and apply them in a state-ofthe-art hierarchical MT system. The features used in this work are non-terminal labels, non-terminal length distribution, source string context and source dependency LM scores. The effectiveness of our techniques is demonstrated by significant improvements over a strong baseline. On Arabic-to-English translation, improvements in lower-cased BLEU are
