Machine Learning
A systematic comparison of various statistical alignment models
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
A note on Platt's probabilistic outputs for support vector machines
Machine Learning
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
Tera-scale translation models via pattern matching
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Labelled dependencies in machine translation evaluation
StatMT '07 Proceedings of the Second Workshop on Statistical Machine Translation
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
Bridging SMT and TM with translation recommendation
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Encouraging consistent translation choices
NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Learning translation consensus with structured label propagation
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Locally training the log-linear model for SMT
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
The trouble with SMT consistency
WMT '12 Proceedings of the Seventh Workshop on Statistical Machine Translation
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We present a discriminative learning method to improve the consistency of translations in phrase-based Statistical Machine Translation (SMT) systems. Our method is inspired by Translation Memory (TM) systems which are widely used by human translators in industrial settings. We constrain the translation of an input sentence using the most similar 'translation example' retrieved from the TM. Differently from previous research which used simple fuzzy match thresholds, these constraints are imposed using discriminative learning to optimise the translation performance. We observe that using this method can benefit the SMT system by not only producing consistent translations, but also improved translation outputs. We report a 0.9 point improvement in terms of BLEU score on English--Chinese technical documents.