Abstract
Mongolian text proofreading is the particularly difficult task because of its unique polyphonic alphabet, morphological ambiguity and agglutinative feature, and coding errors are currently pervasive in the Mongolian corpus of electronic edition, which results in Mongolian statistic and retrieval research toughly difficult to carry out. Some conventional approaches have been proposed to solve this problem but with limitations by not considering proofreading of polyphone. In this paper, we address this problem by means of constructing the large-scale resource and conducting n-gram language model based approach. For ease of understanding, the entire proofreading system architecture is also introduced in this paper, since the polyphone proofreading is the important component of it. Experimental results show that our method performs pretty well. Polyphone correction accuracy is relatively improved by 62% and overall system accuracy is relatively promoted by 16.1%.
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Acknowledgements
This paper is supported by The National Natural Science Foundation of China (No. 61563040), Inner Mongolia Natural Science Foundation of major projects (No. 2016ZD06) and Inner Mongolia Natural Science Fund Project (No. 2017BS0601).
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Lu, M., Bao, F., Gao, G. (2017). Language Model for Mongolian Polyphone Proofreading. In: Sun, M., Wang, X., Chang, B., Xiong, D. (eds) Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data. NLP-NABD CCL 2017 2017. Lecture Notes in Computer Science(), vol 10565. Springer, Cham. https://doi.org/10.1007/978-3-319-69005-6_38
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DOI: https://doi.org/10.1007/978-3-319-69005-6_38
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