Improved Statistical Machine Translation Using Monolingual Paraphrases

Authors:
Preslav Nakov
Affiliations:
Linguistic Modeling Dept. of the Inst. for Parallel Proc. at the Bulgarian Acad. of Sci., Sofia, Bulgaria, email: nakov@lml.bas.bg and Dept. of Math. and Informatics, Sofia Univ., 5, James Bourchi ...
Venue:
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Year:
2008

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Abstract

We propose a novel monolingual sentence paraphrasing method for augmenting the training data for statistical machine translation systems “for free” --by creating it from data that is already available rather than having to create more aligned data. Starting with a syntactic tree, we recursively generate new sentence variants where noun compounds are paraphrased using suitable prepositions, and vice-versa --preposition-containing noun phrases are turned into noun compounds. The evaluation shows an improvement equivalent to 33%--50% of that of doubling the amount of training data.