Maximum entropy based phrase reordering model 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
Discriminative reordering models for statistical machine translation
StatMT '06 Proceedings of the Workshop on Statistical Machine Translation
A direct syntax-driven reordering model for phrase-based machine translation
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Improving reordering for statistical machine translation with smoothed priors and syntactic features
SSST-5 Proceedings of the Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation
Distortion Model Based on Word Sequence Labeling for Statistical Machine Translation
ACM Transactions on Asian Language Information Processing (TALIP)
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We propose a distance phrase reordering model (DPR) for statistical machine translation (SMT), where the aim is to capture phrase reorderings using a structure learning framework. On both the reordering classification and a Chinese-to-English translation task, we show improved performance over a baseline SMT system.