In this paper, we introduce a synchronous bidirectional-neural machine translation (SB-NMT) that predicts its outputs using left-to-right and right-to-left decoding simultaneously and interactively, in order to leverage both of the history and future information at the same time.
we first propose a new algorithm that enables synchronous bidirectional decoding in a single model.