Wei-Chieh Chou


2018

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以深層類神經網路標記中文階層式多標籤語意概念 (Hierarchical Multi-Label Chinese Word Semantic Labeling using Deep Neural Network)
Wei-Chieh Chou | Yih-Ru Wang
International Journal of Computational Linguistics & Chinese Language Processing, Volume 23, Number 2, December 2018

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以深層類神經網路標記中文階層式多標籤語意概念 (Hierarchical Multi-Label Chinese Word Semantic Labeling using Deep Neural Network ) [In Chinese]
Wei-Chieh Chou | Yih-Ru Wang
Proceedings of the 30th Conference on Computational Linguistics and Speech Processing (ROCLING 2018)

2016

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Word Order Sensitive Embedding Features/Conditional Random Field-based Chinese Grammatical Error Detection
Wei-Chieh Chou | Chin-Kui Lin | Yuan-Fu Liao | Yih-Ru Wang
Proceedings of the 3rd Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA2016)

This paper discusses how to adapt two new word embedding features to build a more efficient Chinese Grammatical Error Diagnosis (CGED) systems to assist Chinese foreign learners (CFLs) in improving their written essays. The major idea is to apply word order sensitive Word2Vec approaches including (1) structured skip-gram and (2) continuous window (CWindow) models, because they are more suitable for solving syntax-based problems. The proposed new features were evaluated on the Test of Chinese as a Foreign Language (TOCFL) learner database provided by NLP-TEA-3&CGED shared task. Experimental results showed that the new features did work better than the traditional word order insensitive Word2Vec approaches. Moreover, according to the official evaluation results, our system achieved the lowest (0.1362) false positive (FA) and the highest precision rates in all three measurements.