Multidirectional recurrent neural network machine translation model training method and device

The invention discloses a multi-directional recurrent neural network machine translation model training method and device, and relates to the field of machine translations, the multi-directional recurrent neural network machine translation model comprises initial translation, recurrent source end translation and recurrent target end translation, during training, the characteristics of parallel data are utilized, in a training stage, a source end sentence sequence and a target end sentence sequence are regenerated through a translation model, and part of parameters of an initial translation model are optimized by calculating loss of the sentence sequence generated through reconstruction so as to improve performance in the initial translation model. calculating the similarity between the context vector of the sentence sequence obtained by different reconstructions and the context vector of the source end sentence or the context vector of the target end sentence output by the initial translation model. 本发明公开了一种多