Improving the Efficiency of Grammatical Error Correction with Erroneous Span Detection and Correction
This addresses efficiency issues for users of grammatical error correction systems, though it is incremental as it builds on existing seq2seq methods.
The paper tackled the problem of improving efficiency in Grammatical Error Correction by proposing a two-step approach involving erroneous span detection and correction, achieving comparable performance to conventional methods with less than 50% inference time cost.
We propose a novel language-independent approach to improve the efficiency for Grammatical Error Correction (GEC) by dividing the task into two subtasks: Erroneous Span Detection (ESD) and Erroneous Span Correction (ESC). ESD identifies grammatically incorrect text spans with an efficient sequence tagging model. Then, ESC leverages a seq2seq model to take the sentence with annotated erroneous spans as input and only outputs the corrected text for these spans. Experiments show our approach performs comparably to conventional seq2seq approaches in both English and Chinese GEC benchmarks with less than 50% time cost for inference.