A systematic comparison of various statistical alignment models
Computational Linguistics
The mathematics of statistical machine translation: parameter estimation
Computational Linguistics - Special issue on using large corpora: II
Finding structural correspondences from bilingual parsed corpus for corpus-based translation
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
A syntax-based statistical translation model
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Loosely tree-based alignment for machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for 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
DMMT '01 Proceedings of the workshop on Data-driven methods in machine translation - Volume 14
Dependency treelet translation: syntactically informed phrasal SMT
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Non-projective dependency parsing using spanning tree algorithms
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
A fully-lexicalized probabilistic model for Japanese syntactic and case structure analysis
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
A discriminative model for tree-to-tree translation
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
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When aligning very different language pairs, the most important needs are the use of structural information and the capability of generating one-to-many or many-to-many correspondences. In this paper, we propose a novel phrase alignment method which models word or phrase dependency relations in dependency tree structures of source and target languages. The dependency relation model is a kind of tree-based reordering model, and can handle non-local reorderings which sequential word-based models often cannot handle properly. The model is also capable of estimating phrase correspondences automatically without any heuristic rules. Experimental results of alignment show that our model could achieve F-measure 1.7 points higher than the conventional word alignment model with symmetrization algorithms