Paper: Better Filtration and Augmentation for Hierarchical Phrase-Based Translation Rules

ACL ID P10-2026
Title Better Filtration and Augmentation for Hierarchical Phrase-Based Translation Rules
Venue Annual Meeting of the Association of Computational Linguistics
Session Short Paper
Year 2010
Authors

This paper presents a novel filtration cri- terion to restrict the rule extraction for the hierarchical phrase-based translation model, where a bilingual but relaxed well- formed dependency restriction is used to filter out bad rules. Furthermore, a new feature which describes the regularity that the source/target dependency edge trig- gers the target/source word is also pro- posed. Experimental results show that, the new criteria weeds out about 40% rules while with translation performance im- provement, and the new feature brings an- other improvement to the baseline system, especially on larger corpus.