Chinese Grammatical Correction Using BERT-based Pre-trained Model

Asian Chapter of the Association for Computational Linguistics 2020 · Hongfei Wang, Michiki Kurosawa, Satoru Katsumata, Mamoru Komachi ·

In recent years, pre-trained models have been extensively studied, and several downstream tasks have benefited from their utilization. In this study, we verify the effectiveness of two methods that incorporate a BERT-based pre-trained model developed by Cui et al. (2020) into an encoder-decoder model on Chinese grammatical error correction tasks. We also analyze the error type and conclude that sentence-level errors are yet to be addressed.