To this end, we propose a Transformer NMT model that incorporates dependency relations into self-attention on both source and target sides.
in training, a part of self-attention is learned with constraints based on dependency relations of source or target sentences to attend to a modifiee for each token, and, in decoding, the proposed model translates a sentence in consideration of dependency relations in both the source and target sides, which are captured by our self-attention mechanisms.