Learning Linear Ordering Problems for Better Translation

  title={Learning Linear Ordering Problems for Better Translation},
  author={Roy W. Tromble and Jason Eisner},
We apply machine learning to the Linear Ordering Problem in order to learn sentence-specific reordering models for machine translation. We demonstrate that even when these models are used as a mere preprocessing step for German-English translation, they significantly outperform Moses’ integrated lexicalized reordering model. Our models are trained on automatically aligned bitext. Their form is simple but novel. They assess, based on features of the input sentence, how strongly each pair of… CONTINUE READING
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