Paper: Partial Matching Strategy for Phrase-based Statistical Machine Translation

ACL ID P08-2041
Title Partial Matching Strategy for Phrase-based Statistical Machine Translation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

This paper presents a partial matching strat- egy for phrase-based statistical machine trans- lation (PBSMT). Source phrases which do not appear in the training corpus can be trans- lated by word substitution according to par- tially matched phrases. The advantage of this method is that it can alleviate the data sparse- ness problem if the amount of bilingual corpus is limited. We incorporate our approach into the state-of-the-art PBSMT system Moses and achieve statistically significant improvements on both small and large corpora.