Paper: Using Similarity Scoring To Improve The Bilingual Dictionary For Sub-Sentential Alignment

ACL ID P02-1052
Title Using Similarity Scoring To Improve The Bilingual Dictionary For Sub-Sentential Alignment
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2002
Authors

We describe an approach to improve the bilingual cooccurrence dictionary that is used for word alignment, and evaluate the improved dictionary using a version of the Competitive Linking algorithm. We demonstrate a problem faced by the Com- petitive Linking algorithm and present an approach to ameliorate it. In particular, we rebuild the bilingual dictionary by cluster- ing similar words in a language and as- signing them a higher cooccurrence score with a given word in the other language than each single word would have other- wise. Experimental results show a signifi- cant improvement in precision and recall for word alignment when the improved dicitonary is used.