Abstract:The Grammatical Error Correction (GEC) task is to realize automatic error detection and correction of text through natural language processing technology, such as word order, spelling and other grammatical errors. Many existing Chinese GEC methods have achieved good results, but these methods have not taken into characteristics of learners, such as level,native language and so on. Therefore, this paper proposes to personalize the GEC model to the characteristics of Chinese as a Second Language (CSL) learners and correct the mistakes made by CSL learners with different characteristics. To verify our method, we construct domain adaptation datasets. Experiment results on the domain adaptation datasets demonstrate that the performance of the GEC model is greatly improved after adapting to various domains of CSL learners.
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