(untitled) (International Conference on Computers in Education, 2020)
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.