Paper: Forest-Based Translation

ACL ID P08-1023
Title Forest-Based Translation
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2008
Authors

Among syntax-based translation models, the tree-based approach, which takes as input a parse tree of the source sentence, is a promis- ing direction being faster and simpler than its string-based counterpart. However, current tree-based systems suffer from a major draw- back: they only use the 1-best parse to direct the translation, which potentially introduces translation mistakes due to parsing errors. We propose a forest-based approach that trans- lates a packed forest of exponentially many parses, which encodes many more alternatives than standard n-best lists. Large-scale exper- iments show an absolute improvement of 1.7 BLEU points over the 1-best baseline. This result is also 0.8 points higher than decoding with 30-best parses, and takes even less time.