Neural Name Translation Improves Neural Machine Translation

Understand

In order to control computational complexity, neural machine translation (NMT) systems convert all rare words outside the vocabulary into a single unk symbol.

• Previous solution (Luong et al., 2015) resorts to use multiple numbered unks to learn the correspondence between source and target rare words.
• However, testing words unseen in the training corpus cannot be handled by this method.
• And it also suffers from the noisy word alignment.