Chan-Kun Yeh


2016

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Grammatical Error Detection Based on Machine Learning for Mandarin as Second Language Learning
Jui-Feng Yeh | Tsung-Wei Hsu | Chan-Kun Yeh
Proceedings of the 3rd Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA2016)

Mandarin is not simple language for foreigner. Even using Mandarin as the mother tongue, they have to spend more time to learn when they were child. The following issues are the reason why causes learning problem. First, the word is envolved by Hieroglyphic. So a character can express meanings independently, but become a word has another semantic. Second, the Mandarin’s grammars have flexible rule and special usage. Therefore, the common grammatical errors can classify to missing, redundant, selection and disorder. In this paper, we proposed the structure of the Recurrent Neural Networks using Long Short-term memory (RNN-LSTM). It can detect the error type from the foreign learner writing. The features based on the word vector and part-of-speech vector. In the test data found that our method in the detection level of recall better than the others, even as high as 0.9755. That is because we give the possibility of greater choice in detecting errors.

2015

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Automatic Classification of the “De” Word Usage for Chinese as a Foreign Language
Jui-Feng Yeh | Chan-Kun Yeh
International Journal of Computational Linguistics & Chinese Language Processing, Volume 20, Number 1, June 2015-Special Issue on Chinese as a Foreign Language

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Condition Random Fields-based Grammatical Error Detection for Chinese as Second Language
Jui-Feng Yeh | Chan-Kun Yeh | Kai-Hsiang Yu | Ya-Ting Li | Wan-Ling Tsai
Proceedings of the 2nd Workshop on Natural Language Processing Techniques for Educational Applications