@inproceedings{d587337d145f4c6493ceb395aee74f89,
title = "Evaluating the Performance of Chinese Multi-Label Grammatical Error Detection Using Deep Neural Networks",
abstract = "In this paper, we describe the process of building a benchmark data set for Chinese multi-label grammatical error detection tasks, comparing the performance of 10 representative neural network models. Experimental results reveal that no matter which deep learning model is used, the performance is still limited which confirms the difficulty of the multi-label detection task. Our constructed datasets and evaluation results will be publicly released on the GitHub repository (https://github.com/NCUEE-NLPLab/CMLGED) to promote further research to facilitate technology-enhanced Chinese learning.",
keywords = "deep learning, Grammatical error detection, multi-label classification",
author = "Lin, {Tzu Mi} and Chen, {Chao Yi} and Lee, {Lung Hao} and Tseng, {Yuen Hsien}",
note = "Publisher Copyright: {\textcopyright} 30th International Conference on Computers in Education Conference, ICCE 2022 - Proceedings.; 30th International Conference on Computers in Education Conference, ICCE 2022 ; Conference date: 28-11-2022 Through 02-12-2022",
year = "2022",
month = nov,
day = "28",
language = "???core.languages.en_GB???",
series = "30th International Conference on Computers in Education Conference, ICCE 2022 - Proceedings",
publisher = "Asia-Pacific Society for Computers in Education",
pages = "524--526",
editor = "Sridhar Iyer and Ju-Ling Shih and Ju-Ling Shih and Weiqin Chen and Weiqin Chen and Khambari, {Mas Nida MD} and Mouna Denden and Rwitajit Majumbar and Medina, {Liliana Cuesta} and Shitanshu Mishra and Sahana Murthy and Patcharin Panjaburee and Daner Sun",
booktitle = "30th International Conference on Computers in Education Conference, ICCE 2022 - Proceedings",
}