Word Alignment with Synonym Regularization

We present a novel framework for word alignment that incorporates synonym knowledge collected from monolingual linguistic resources in a bilingual probabilistic model. Synonym information is helpful for word alignment because we can expect a synonym to correspond to the same word in a different language. We design a generative model for word alignment that uses synonym information as a regularization term. The experimental results show that our proposed method significantly improves word alignment quality.

• Type: Journal
• Year: 2010
• Where: ACL
• Authors: Hiroyuki Shindo, Akinori Fujino, Masaaki Nagata
• Keywords: ACL 2010, Computational Linguistics, Synonym Information, Word Alignment, Word Alignment Quality