Grammatical Error Correction by Transferring Learning Based on Pre-Trained Language Model
Grammatical error correction (GEC) is a low-resource task, which requires annotations with high costs and is time consuming in training.In this paper, the MASS-GEC is proposed to solve this problem by transferring learning from a pre-trained language generation model, and masked LIP SHIMMER CARAMEL sequence is proposed to sequence pre-training for