Paper: A Probability Model To Improve Word Alignment

ACL ID P03-1012
Title A Probability Model To Improve Word Alignment
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2003
Authors

Word alignment plays a crucial role in sta- tistical machine translation. Word-aligned corpora have been found to be an excellent source of translation-related knowledge. We present a statistical model for comput- ing the probability of an alignment given a sentence pair. This model allows easy in- tegration of context-specific features. Our experiments show that this model can be an effective tool for improving an existing word alignment.