Paper: Model With Minimal Translation Units, But Decode With Phrases

ACL ID N13-1001
Title Model With Minimal Translation Units, But Decode With Phrases
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2013
Authors

N-gram-based models co-exist with their phrase-based counterparts as an alternative SMT framework. Both techniques have pros and cons. While the N-gram-based frame- work provides a better model that captures both source and target contexts and avoids spurious phrasal segmentation, the ability to memorize and produce larger translation units gives an edge to the phrase-based systems dur- ing decoding, in terms of better search per- formance and superior selection of transla- tion units. In this paper we combine N-gram- based modeling with phrase-based decoding, and obtain the benefits of both approaches. Our experiments show that using this combi- nation not only improves the search accuracy of the N-gram model but that it also improves the BLEU scores. Our system outperforms state-of-the-a...