Chinese Grammatical Correction Using BERT-based Pre-trained Model
This work tackles grammatical correction for Chinese language users, but it is incremental as it builds on existing models without major breakthroughs.
The study tested two methods integrating a BERT-based pre-trained model into an encoder-decoder model for Chinese grammatical error correction, finding that sentence-level errors remain unaddressed.
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.