@inproceedings{565e1a1139924c84b801e788e6af79b9,
title = "Chinese grammatical error detection using a CNN-LSTM model",
abstract = "In this paper, we proposed a Convolution Neural Network with Long Short-Term Memory (CNN-LSTM) model for Chinese grammatical error detection. The TOCFL learner corpus is adopted to measure the system performance of indicating whether a sentence contains errors or not. Our model performs better than other neural network based methods in terms of accuracy for identifying an erroneous sentence written by Chinese language learners.",
keywords = "Chinese as a foreign language, Deep neural networks, Grammatical error diagnosis",
author = "Lee, {Lung Hao} and Lin, {Bo Lin} and Yu, {Liang Chih} and Tseng, {Yuen Hsien}",
note = "Publisher Copyright: {\textcopyright} 2017 Asia-Pacific Society for Computers in Education. All rights reserved.; 25th International Conference on Computers in Education, ICCE 2017 ; Conference date: 04-12-2017 Through 08-12-2017",
year = "2017",
language = "English",
isbn = "9789869401265",
series = "Proceedings of the 25th International Conference on Computers in Education, ICCE 2017 - Main Conference Proceedings",
publisher = "Asia-Pacific Society for Computers in Education",
pages = "919--921",
editor = "{Mohd Ayub}, {Ahmad Fauzi} and Antonija Mitrovic and Jie-Chi Yang and Wong, {Su Luan} and Wenli Chen",
booktitle = "Proceedings of the 25th International Conference on Computers in Education, ICCE 2017 - Main Conference Proceedings",
}