基于深度学习的语法纠错技术研究进展

Research progress on grammatical error correction technique based on deep learning

语法纠错(GEC)旨在自动检测并纠正文本中的语法错误,从而提升文本的质量和可读性。文章首先总结了语法纠错技术的研究进展和主要研究成果;其次针对当前纠错任务存在的泛化能力差、高质量数据缺乏、语法错误复杂、运行速度慢等问题,分析了基于当前主流深度学习模型Transformer的优化改进方案;最后指出了当前语法纠错技术面临的挑战及可行的研究方向。

Grammar Error Correction(GEC)aims to automatically detect and correct grammar errors in text,thereby improving the quality and readability of the text.The article first summarizes the research progress and main achievements of grammar correction techniques.Secondly,in response to the problems of poor generalization ability,lack of high-quality data,complex syntax errors,and slow running speed in current error correction tasks,an optimization and improvement plan based on the mainstream deep learning model Transformer was analyzed.Finally,the challenges and feasible research directions faced by current grammar correction techniques were pointed out.