Abstract
Tibetan word segmentation (TWS) is the basic problem for Tibetan natural language processing. The paper reformulates the segmentation as a syllable tagging problem, and studies the performance of TWS with different sequence labeling models. Experimental results show that, the TWS system with conditional random field achieves the best performance in the condition of current 4-tag set, at the same time, the other models achieve good results too. All the above show that, the segmentation as a syllable tagging problem that is an efficient approach to deal with TWS.
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Li, Y., Yu, H. (2013). Study on Tibetan Word Segmentation as Syllable Tagging. In: Zhou, G., Li, J., Zhao, D., Feng, Y. (eds) Natural Language Processing and Chinese Computing. NLPCC 2013. Communications in Computer and Information Science, vol 400. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41644-6_34
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DOI: https://doi.org/10.1007/978-3-642-41644-6_34
Publisher Name: Springer, Berlin, Heidelberg
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