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This thesis studies the disambiguation method in Uyghur-Chinese translation, and proposes the design philosophy
of automatic-acquisition in translation label library aiming at the deficiency of disambiguation corpus in Uyghur.
It refers to the existing Uyghur-Chinese bilingual dictionary, Chinese corpus and the Internet, and acquires the corresponding
Chinese translation label examples to Uyghur automatically. On this basis, this thesis designs a Uyghur-Chinese
disambiguation model, and refines the meaning probability definition based on HMM model. It increases the model’s
backwards-dependence, and the model’s ability to obtain contextual information. To use the model to learn disambiguation
knowledge from translation label corpus can eliminate the ambiguity in new Uyghur ambiguous words. From the experiment
result, it can prove that the Uyghur-Chinese translation disambiguation framework based on automatically acquired
corpus is effective, and increases with the increasing of the scale of translation label corpus, degree of accuracy of
the disambiguation result also increases accordingly.