A Probability Model to Improve Word Alignment

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

• Type: Conference
• Year: 2003
• Where: ACL
• Authors: Colin Cherry, Dekang Lin
• Keywords: ACL 2003, ACL 2007, Model, Statistical Machine Translation, Word Alignment