2017

Exploiting Cross-Sentence Context for Neural Machine Translation

Wang, Longyue, Tu, Zhaopeng, Way, Andy et al.

Understand

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.

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