Papers with pre-ordering model

1 papers
Exploiting Pre-Ordering for Neural Machine Translation (L18-1)

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Challenge: Existing studies have shown that Neural Machine Translation suffers from the problems that some source words are mistakenly translated for multiple times .
Approach: They propose a pre-ordering approach to solve the under-translation problem by pre-ordnanced source sentences and position embedding to enhance monotone translation.
Outcome: The proposed method significantly improves translation quality by 2.43 BLEU points on Chinese-to-English translation.

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