Uyghur-to-Chinese Neural Machine Translation Based on Incremental Training

At present,the neural machine translation based on deep learning has become the mainstream method in the field of machine translation.The neural machine translation model requires a larger parameter size than the statistical machine translation model does. Therefore, its translation quality depends on the sufficiency of the training data.Due to the serious lack of parallel corpus resources related to Uyghur,the neural machine translation model performs poorly on Uyghur-to-Chinese translation tasks.This paper proposes a method of incremental training of neural machine translation models using pseudo-corpus,which effectively improves the quality of neural machine translation in Uyghur-to-Chinese translation tasks.