Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
A class-based approach to word alignment
Computational Linguistics
Stochastic inversion transduction grammars and bilingual parsing of parallel corpora
Computational Linguistics
A simple hybrid aligner for generating lexical correspondences in parallel texts
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
A probability model to improve word alignment
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Improved statistical alignment models
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
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This paper proposes an approach to improve word alignment in a specific domain, in which only a small-scale domain-specific corpus is available, by adapting the word alignment information in the general domain to the specific domain. This approach first trains two statistical word alignment models with the large-scale corpus in the general domain and the small-scale corpus in the specific domain respectively, and then improves the domain-specific word alignment with these two models. Experimental results show a significant improvement in terms of both alignment precision and recall. And the alignment results are applied in a computer assisted translation system to improve human translation efficiency.