Combining labeled and unlabeled data with co-training
COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
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
HMM-based word alignment in statistical translation
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
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
Tri-Training: Exploiting Unlabeled Data Using Three Classifiers
IEEE Transactions on Knowledge and Data Engineering
Statistical machine translation with word- and sentence-aligned parallel corpora
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Log-linear models for word alignment
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Semi-supervised training for statistical word alignment
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
A discriminative matching approach to word alignment
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
A discriminative framework for bilingual word alignment
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
A maximum entropy approach to combining word alignments
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Soft syntactic constraints for word alignment through discriminative training
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Boosting statistical word alignment using labeled and unlabeled data
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Measuring Word Alignment Quality for Statistical Machine Translation
Computational Linguistics
Better word alignments with supervised ITG models
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
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Supervised learning has been recently used to improve the performance of word alignment. However, due to the limited amount of labeled data, the performance of "pure" supervised learning, which only used labeled data, is limited. As a result, many existing methods employ features learnt from a large amount of unlabeled data to assist the task. In this paper, we propose a semi-supervised ensemble method to better incorporate both labeled and unlabeled data during learning. Firstly, we employ an ensemble learning framework, which effectively uses alignment results from different unsupervised alignment models. We then propose to use a semi-supervised learning method, namely Tri-training, to train classifiers using both labeled and unlabeled data collaboratively and further improve the result. Experimental results show that our methods can substantially improve the quality of word alignment. The final translation quality of a phrase-based translation system is slightly improved, as well.