Abstract
For low-resource languages like Uyghur, data sparseness is always a serious problem in related information processing, especially in some tasks based on parallel texts. To enrich bilingual resources, we detect Chinese and Russian loan words from Uyghur texts according to phonetic similarities between a loan word and its corresponding donor language word. In this paper, we propose a novel approach based on perceptron model to discover loan words from Uyghur texts, which consider the detection of loan words in Uyghur as a classification procedure. The experimental results show that our method is capable of detecting the Chinese and Russian loan words in Uyghur Texts effectively.
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