Voting on N-grams for Machine Translation System Combination

Abstract

System combination exploits differences between machine translation systems to form a combined translation from several system outputs. Core to this process are features that reward n-gram matches between a candidate combination and each system output. Systems differ in performance at the n-gram level despite similar overall scores. We therefore advocate a new feature formulation: for each system and each small n, a feature counts n-gram matches between the system and candidate. We show post-evaluation improvement of 6.67 BLEU over the best system on NIST MT09 Arabic-English test data. Compared to a baseline system combination scheme from WMT 2009, we show improvement in the range of 1 BLEU point.

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@inproceedings{Heafield2010VotingON, title={Voting on N-grams for Machine Translation System Combination}, author={Kenneth Heafield and Alon Lavie}, year={2010} }