Design and Implementation of English Grammar Error Correction System Based on Deep Learning

Abstract

At present, our English error correction algorithm is slightly general, the error correction ability is also very limited, and its accuracy rate is also low, so it is very necessary to improve. This article will further explore the problem of syntax error correction, and the corresponding algorithm model will also be proposed. Based on deep learning technology to improve the error correction rate of English grammar, put forward the corresponding solution, put forward the Sep2seq-based English grammar error correction system model, and carry out a series of rectifications to improve its efficiency and accuracy. The basic architecture of TensorFLOW is used to implement the model, and the success of the error correction algorithm model is proved, which brings great improvement and progress to the success of error correction.