SB-NMT: Synchronous Bidirectional NMT

SB NMT stands for “Synchronous Bi-directional Neural Machine Translation” which is a model proposed by the the University of Chinese Academy of Sciences in 2019 and published in their paper under the same name: Synchronous Bidirectional Neural Machine Translation. The official code for this paper can be found on the following GitHub repository: sb-nmt.

SB-NMT architecture is the same as the standard Transformer with the exception that the decoder has a Synchronous Bi-directional Attention sub-layer instead of the Multi-head Self-attention one which enable the decoder to predict 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.