Detection of Chinese Grammatical Errors with Context Representation

摘要

With the rapid development of China, more and more non-native Chinese speakers begin to learn Chinese. Therefore, the task of detecting Chinese grammatical error has got more and more attention. However, most current detection methods focus on building more complex detection models and adding artificial features, ignore the effect of polysemic words in Chinese text. In this paper, we propose a Chinese grammatical error detection model to handle the ambiguity problems of Chinese words. Compared with the baseline model, our model achieves better results on accuracy, MRR, HIT@2 and HIT@20%.