An introduction to variational methods for graphical models
Learning in graphical models
Computational Complexity of Problems on Probabilistic Grammars and Transducers
ICGI '00 Proceedings of the 5th International Colloquium on Grammatical Inference: Algorithms and Applications
Computational complexity of probabilistic disambiguation by means of tree-grammars
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 2
Parameter estimation for probabilistic finite-state transducers
ACL '02 Proceedings of the 40th 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
Generalized algorithms for constructing statistical language models
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - 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
Improved statistical alignment models
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
A General Technique to Train Language Models on Language Models
Computational Linguistics
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Probabilistic CFG with latent annotations
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
A better N-best list: practical determinization of weighted finite tree automata
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Hierarchical Phrase-Based Translation
Computational Linguistics
Minimum risk annealing for training log-linear models
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Lattice Minimum Bayes-Risk decoding for statistical machine translation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
SSST '08 Proceedings of the Second Workshop on Syntax and Structure in Statistical Translation
Joshua: an open source toolkit for parsing-based machine translation
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
N-gram posterior probabilities for statistical machine translation
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
Fast consensus decoding over translation forests
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
Demonstration of Joshua: an open source toolkit for parsing-based machine translation
ACLDemos '09 Proceedings of the ACL-IJCNLP 2009 Software Demonstrations
Fast consensus decoding over translation forests
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
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Graphical models over multiple strings
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Consensus training for consensus decoding in machine translation
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
Expected sequence similarity maximization
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Model combination for machine translation
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
A unified approach to minimum risk training and decoding
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
ATANLP '10 Proceedings of the 2010 Workshop on Applications of Tree Automata in Natural Language Processing
Fluency constraints for minimum Bayes-risk decoding of statistical machine translation lattices
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Monte Carlo techniques for phrase-based translation
Machine Translation
Minimum Bayes-risk system combination
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
A decoding method of system combination based on hypergraph in SMT
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III
Fast generation of translation forest for large-scale SMT discriminative training
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Minimum imputed risk: unsupervised discriminative training for machine translation
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Third-order variational reranking on packed-shared dependency forests
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Tree parsing with synchronous tree-adjoining grammars
IWPT '11 Proceedings of the 12th International Conference on Parsing Technologies
Trait-based hypothesis selection for machine translation
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Deciding the twins property for weighted tree automata over extremal semifields
ATANLP '12 Proceedings of the Workshop on Applications of Tree Automata Techniques in Natural Language Processing
Improving NLP through marginalization of hidden syntactic structure
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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Statistical models in machine translation exhibit spurious ambiguity. That is, the probability of an output string is split among many distinct derivations (e.g., trees or segmentations). In principle, the goodness of a string is measured by the total probability of its many derivations. However, finding the best string (e.g., during decoding) is then computationally intractable. Therefore, most systems use a simple Viterbi approximation that measures the goodness of a string using only its most probable derivation. Instead, we develop a variational approximation, which considers all the derivations but still allows tractable decoding. Our particular variational distributions are parameterized as n-gram models. We also analytically show that interpolating these n-gram models for different n is similar to minimum-risk decoding for BLEU (Tromble et al., 2008). Experiments show that our approach improves the state of the art.