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Exploiting Cross-Sentence Context for Neural Machine Translation

Abstract · Apr 14, 2017 04:56 ·

coder nmt sentence cross source context decoder translation history cs-cl

Arxiv Abstract

  • Longyue Wang
  • Zhaopeng Tu
  • Andy Way
  • Qun Liu

In translation, considering the document as a whole can help to resolve ambiguities and inconsistencies. In this paper, we propose a cross-sentence context-aware approach and investigate the influence of historical contextual information on the performance of neural machine translation (NMT). First, this history is summarized in a hierarchical way. We then integrate the historical representation into NMT in two strategies: 1) a warm-start of encoder and decoder states, and 2) an auxiliary context source for updating decoder states. Experimental results on a large Chinese-English translation task show that our approach significantly improves upon a strong attention-based NMT system by up to +2.1 BLEU points.

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