@inproceedings{1286d24bec3c455da7d8a66031182fbe,
title = "Multi-Channel CNN-BiLSTM for Chinese grammatical error detection",
abstract = "In this paper, we proposed a Multi-Channel Convolutional Neural Network with Bidirectional Long Short-Term Memory (MC-CNN-BiLSTM) model for Chinese grammatical error detection. The TOCFL learner corpus is adopted to measure the system capability of indicating whether a sentence contains errors or not. Our model performs better than a previous CNN-LSTM model that reflects the effectiveness of multi-channel embedding representation.",
keywords = "Chinese as a foreign language, Deep neural networks, Grammatical error diagnosis",
author = "Lee, {Lung Hao} and Wang, {Yuh Shyang} and Lin, {Po Chen} and Hung, {Chih Te} and Tseng, {Yuen Hsien}",
note = "Funding Information: This study was partially supported by the Ministry of Science and Technology, under the grant 109-2410-H-003-123-MY3, 108-2218-E-008-017-MY3, and 106-2221-E-003-030-MY2. Publisher Copyright: {\textcopyright} ICCE 2020 - 28th International Conference on Computers in Education, Proceedings. All rights reserved.; 28th International Conference on Computers in Education, ICCE 2020 ; Conference date: 23-11-2020 Through 27-11-2020",
year = "2020",
month = nov,
day = "23",
language = "English",
series = "ICCE 2020 - 28th International Conference on Computers in Education, Proceedings",
publisher = "Asia-Pacific Society for Computers in Education",
pages = "558--560",
editor = "Hyo-Jeong So and Rodrigo, {Ma. Mercedes} and Jon Mason and Antonija Mitrovic and Daniel Bodemer and Weichao Chen and Zhi-Hong Chen and Brendan Flanagan and Marc Jansen and Roger Nkambou and Longkai Wu",
booktitle = "ICCE 2020 - 28th International Conference on Computers in Education, Proceedings",
}