A Probability Model to Improve Word Alignment
- Colin Cherry ,
- Dekang Lin
Proceedings of the 41st Annual Meeting of the Association for Computational Linguistics |
Published by Association for Computational Linguistics
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.