In this paper, we propose a novel model for Transformer neural machine translation that incorporates syntactic distances between two source words into the relative position representations of a selfattention mechanism.
the proposed model encodes pair-wise relative depths on a source dependency tree, which are the differences between the depths of two source words, in the encoder's selfattention.