Paper: A Maximum Entropy Approach To Combining Word Alignments

ACL ID N06-1013
Title A Maximum Entropy Approach To Combining Word Alignments
Venue Human Language Technologies
Session Main Conference
Year 2006
Authors

This paper presents a new approach to combining outputs of existing word align- ment systems. Each alignment link is rep- resented with a set of feature functions extracted from linguistic features and in- put alignments. These features are used as the basis of alignment decisions made by a maximum entropy approach. The learning method has been evaluated on three language pairs, yielding significant improvements over input alignments and three heuristic combination methods. The impact of word alignment on MT quality is investigated, using a phrase-based MT system.