Research on Computer Intelligent Proofreading System for English Translation Based on Deep Learning

Abstract

English, as a global language, is widely used in daily life, which leads to higher requirements for people's language proficiency. Grammar, as an essential part of English, plays a significant role in language acquisition. Although the needs for English learning have become greater, the resources of English teaching are quite limited. Under this circumstance, it is imperative to apply information technology to alleviate the burden of lacking sufficient educational resources. The intelligent grammar correction system is in special needs. In this study therefore, the deep learning-based CNN and RNN bidirectional propagation model were utilized to construct a feedback filtering function, screen the suggested text, and select the high-quality suggested text for the retraining of the error correction model. The proofreading optimization algorithm and feedback filtering algorithm were used in practice to implement each functional module. The core function service module was designed with a cluster deployment scheme with high system performance and response speed to ensure system stability and availability. Experimental results demonstrate that the correct rate gradually increased with increasing the number of tests and finally stabilized at about 86%. The overall average correcting rate obtained from the present model was verified to be superior to that from the GRU model and the MGB model.