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
A syntax-based statistical translation model
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th 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
Minimum error rate training in statistical machine translation
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
A hierarchical phrase-based model for statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Distortion models for statistical machine translation
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Symmetric word alignments for statistical machine translation
COLING '04 Proceedings of the 20th international conference on 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
Measuring Word Alignment Quality for Statistical Machine Translation
Computational Linguistics
Using a dependency parser to improve SMT for subject-object-verb languages
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Diversify and combine: improving word alignment for machine translation on low-resource languages
ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
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Most existing techniques for combining multiple alignment tables can combine only two alignment tables at a time, and are based on heuristics (Och and Ney, 2003), (Koehn et al., 2003). In this paper, we propose a novel mathematical formulation for combining an arbitrary number of alignment tables using their power mean. The method frames the combination task as an optimization problem, and finds the optimal alignment lying between the intersection and union of multiple alignment tables by optimizing the parameter p: the affinely extended real number defining the order of the power mean function. The combination approach produces better alignment tables in terms of both F-measure and BLEU scores.