Source Dependency-Aware Transformer with Supervised Self-Attention
Table 2: Evaluation results on the English-to-Japanese translation task.
['System', 'BLEU', 'RIBES']
We conduct experiments on the WAT2016 English-to-Japanese translation task in this section. Our baseline systems include RNNsearch, a tree2seq attentional NMT model using tree-LSTM proposed by Eriguchi et al. (2016) and Transformer. According to the table, our Transformer+CSH and Transformer+PSH outperform Transformer and the other existing NMT models in terms of both BLEU and RIBES.