The invention discloses a neural machine translation system based on Romatized Uygur language, which provides bilingual data with segmented words and proper format for subsequent word alignment processing, for Chinese-Uygur language before constructing a translation system; according to the preprocessing of the system, different preprocessing processes are carried out on corpora according to different characteristics of the corpora, namely Jieba word segmentation is carried out on Chinese corpora, words are continuously cut by using BPE coding, root + affix form word segmentation is firstly carried out on Uygur language corpora, then Roman processing is carried out on Uygur language after word segmentation, and finally processing is carried out by using BPE coding; a translation model is trained by using a Tansformer translation model to obtain a final translation model; for a translation process, firstly, Uygur language is also preprocessed, namely, word segmentation and Roman processing of'word roots + affixes' are carried out, then the processed corpus is translated by using the trained model, and finally translated Chinese is obtained.