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Abstract
Abstract Using computer programs to correct English grammar can improve the efficiency of English grammar correction, improve the effect of error correction, and reduce the workload of manual error correction. In order to deal with and solve the problem of loss evaluation mismatch in the current mainstream machine translation, this study proposes the application of the deep learning method to propose an algorithm model with high error correction performance. Therefore, the framework of confrontation learning network is introduced to continuously improve the optimization model parameters through the confrontation training of discriminator and generator. At the same time, convolutional neural network is introduced to improve the algorithm training effect, which can make the correction sentences generated by the model generator better in confrontation. In order to verify the performance of the algorithm model, P-value, R-value, F 0.5-value, and MRR-value were selected for the comprehensive evaluation of the model performance index. The simulation results of the CoNLL-2014 test set and Lang-8 test set show that the proposed algorithm model has significant performance improvement compared with the traditional transformer method and can correct the fluency of sentences. It has good application values.
Highlights
Using computer programs to achieve automatic error correction of English grammar can realize the practical significance of high efficiency and accuracy, and can liberate many language teachers from simple grammar correction work to carry out more difficult and complex teaching error correction [3]
In order to solve the problem of English grammar error correction, this study proposes a confrontation network model based on deep learning
The purpose of this study is to solve the problem that the current mainstream English grammar error correction function in machine translation finds it difficult to meet the performance requirements, and to propose a convolutional neural network-based learning algorithm model against network so as to achieve higher and better English grammar error correction function
Summary
English is currently one of the most widely used languages in the world, but some English speakers’ mother tongue is not English. Limited by the different language habits and cultural backgrounds of people in different regions, various grammatical errors often occur in the process of writing and using English [1]. These grammatical errors will bring great trouble to users and information audiences. Using computer programs to achieve automatic error correction of English grammar can realize the practical significance of high efficiency and accuracy, and can liberate many language teachers from simple grammar correction work to carry out more difficult and complex teaching error correction [3]. Automatic error correction in English grammar uses computer technology to set up a program to find and correct text errors, which is of great practical significance. A learning model against the problem is proposed to improve the performance of the English grammar correction model
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