Chinese Grammatical Error Detection Using Adversarial ELECTRA Transformers

Lung Hao Lee, Man Chen Hung, Chao Yi Chen, Rou An Chen, Yuen Hsien Tseng*

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

摘要

We explore transformer-based neural networks for Chinese grammatical error detection. The TOCFL learner corpus is used to measure the model capability of indicating whether a sentence contains errors or not. Experimental results show that ELECTRA transformers which take into account both transformer architecture and adversarial learning technique can achieve promising effectiveness with an improvement of F1-score.

原文英語
主出版物標題29th International Conference on Computers in Education Conference, ICCE 2021 - Proceedings
編輯Maria Mercedes T. Rodrigo, Sridhar Iyer, Antonija Mitrovic, Hercy N. H. Cheng, Dan Kohen-Vacs, Camillia Matuk, Agnieszka Palalas, Ramkumar Rajenran, Kazuhisa Seta, Jingyun Wang
發行者Asia-Pacific Society for Computers in Education
頁面111-113
頁數3
ISBN(電子)9789869721479
出版狀態已發佈 - 2021 11月 22
事件29th International Conference on Computers in Education Conference, ICCE 2021 - Virtual, Online
持續時間: 2021 11月 222021 11月 26

出版系列

名字29th International Conference on Computers in Education Conference, ICCE 2021 - Proceedings
1

會議

會議29th International Conference on Computers in Education Conference, ICCE 2021
城市Virtual, Online
期間2021/11/222021/11/26

ASJC Scopus subject areas

  • 電腦科學(雜項)
  • 教育

指紋

深入研究「Chinese Grammatical Error Detection Using Adversarial ELECTRA Transformers」主題。共同形成了獨特的指紋。

引用此