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ACL
2007

A Discriminative Syntactic Word Order Model for Machine Translation

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A Discriminative Syntactic Word Order Model for Machine Translation
We present a global discriminative statistical word order model for machine translation. Our model combines syntactic movement and surface movement information, and is discriminatively trained to choose among possible word orders. We show that combining discriminative training with features to detect these two different kinds of movement phenomena leads to substantial improvements in word ordering performance over strong baselines. Integrating this word order model in a baseline MT system results in a 2.4 points improvement in BLEU for English to Japanese translation.
Pi-Chuan Chang, Kristina Toutanova
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2007
Where ACL
Authors Pi-Chuan Chang, Kristina Toutanova
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