In order to solve the problem of data sparseness caused by less training corpus in Tibetan-Chinese transliteration,this paper ana-lyzes the alignment granularity of Tibetan-Chinese names as the research object and uses the pronunciation feature to reduce the corresponding re-lationships.The method of transliteration of Tibetan and Chinese names and the design of related experiments is comparable with traditional methods and improve the top-1 accuracy of transliteration of Tibetan and Chinese names to 65.72%.The experimental results show that the method can improve the accuracy of Tibetan-Chinese name translitera-tion.