Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
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
A hierarchical phrase-based model for statistical machine translation
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Moses: open source toolkit for statistical machine translation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Practical structured learning techniques for natural language processing
Practical structured learning techniques for natural language processing
Random restarts in minimum error rate training for statistical machine translation
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Lattice-based minimum error rate training for statistical machine translation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A simple and effective hierarchical phrase reordering model
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
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 1 - Volume 1
Improved models of distortion cost for statistical machine translation
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Exact decoding of phrase-based translation models through Lagrangian relaxation
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Optimal search for minimum error rate training
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
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Minimum error rate training is often the preferred method for optimizing parameters of statistical machine translation systems. MERT minimizes error rate by using a surrogate representation of the search space, such as N-best lists or hypergraphs, which only offer an incomplete view of the search space. In our work, we instead minimize error rate directly by integrating the decoder into the minimizer. This approach yields two benefits. First, the function being optimized is the true error rate. Second, it lets us optimize parameters of translations systems other than standard linear model features, such as distortion limit. Since integrating the decoder into the minimizer is often too slow to be practical, we also exploit statistical significance tests to accelerate the search by quickly discarding unpromising models. Experiments with a phrase-based system show that our approach is scalable, and that optimizing the parameters that MERT cannot handle brings improvements to translation results.