Modeling Coverage for Neural Machine Translation

Understand

Attention mechanism has enhanced state-of-the-art Neural Machine Translation (NMT) by jointly learning to align and translate.

• It tends to ignore past alignment information, however, which often leads to over-translation and under-translation.
• To address this problem, we propose coverage-based NMT in this paper.
• We maintain a coverage vector to keep track of the attention history.