Paper: Guiding Statistical Word Alignment Models With Prior Knowledge

ACL ID P07-1001
Title Guiding Statistical Word Alignment Models With Prior Knowledge
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2007
Authors

We present a general framework to incor- porate prior knowledge such as heuristics or linguistic features in statistical generative word alignment models. Prior knowledge plays a role of probabilistic soft constraints between bilingual word pairs that shall be used to guide word alignment model train- ing. We investigate knowledge that can be derived automatically from entropy princi- ple and bilingual latent semantic analysis and show how they can be applied to im- prove translation performance.