Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
A systematic comparison of various statistical alignment models
Computational Linguistics
Understanding belief propagation and its generalizations
Exploring artificial intelligence in the new millennium
The mathematics of statistical machine translation: parameter estimation
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HMM-based word alignment in statistical translation
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Statistical phrase-based translation
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Shallow parsing with conditional random fields
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An evaluation exercise for word alignment
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ACM Transactions on Information Systems (TOIS)
Discriminative word alignment with conditional random fields
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Training conditional random fields with multivariate evaluation measures
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Improved discriminative bilingual word alignment
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for 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
Word alignment via quadratic assignment
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
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Efficient belief propagation with learned higher-order markov random fields
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
The Universität Karlsruhe translation system for the EACL-WMT 2009
StatMT '09 Proceedings of the Fourth Workshop on Statistical Machine Translation
Weighted alignment matrices for statistical machine translation
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 2 - Volume 2
Consensus versus expertise: a case study of word alignment with Mechanical Turk
CSLDAMT '10 Proceedings of the NAACL HLT 2010 Workshop on Creating Speech and Language Data with Amazon's Mechanical Turk
A semi-supervised word alignment algorithm with partial manual alignments
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
The Karlsruhe Institute for technology translation system for the ACL-WMT 2010
WMT '10 Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR
EMDC: a semi-supervised approach for word alignment
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Discriminative word alignment by linear modeling
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Wider context by using bilingual language models in machine translation
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
The Karlsruhe Institute of Technology translation systems for the WMT 2011
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
A correction model for word alignments
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Fast inference in phrase extraction models with belief propagation
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Training factored PCFGs with expectation propagation
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Joint WMT 2012 submission of the QUAERO project
WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
The Karlsruhe institute of technology translation systems for the WMT 2012
WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
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In this paper a new discriminative word alignment method is presented. This approach models directly the alignment matrix by a conditional random field (CRF) and so no restrictions to the alignments have to be made. Furthermore, it is easy to add features and so all available information can be used. Since the structure of the CRFs can get complex, the inference can only be done approximately and the standard algorithms had to be adapted. In addition, different methods to train the model have been developed. Using this approach the alignment quality could be improved by up to 23 percent for 3 different language pairs compared to a combination of both IBM4-alignments. Furthermore the word alignment was used to generate new phrase tables. These could improve the translation quality significantly.