Automatic Detection of Grammatical Errors in English Verbs Based on RNN Algorithm: Auxiliary Objectives for Neural Error Detection Models.

Yizhou He,Bai Yuan Ding

doi:10.1155/2021/6052873

Abstract

With the rapid development of neural network technology, we have widely used this technology in various fields. In the field of language translation, the research on automatic detection technology of English verb grammatical errors is in a hot stage. The traditional manual detection cannot be applied to the current environment. Therefore, this paper proposes an automatic detection technology of English verb grammatical errors based on recurrent neural network (RNN) algorithm to solve this problem. Firstly, the accuracy and feedback speed of traditional manual detection and recurrent neural network RNN algorithm are compared. Secondly, a detection model which can be calculated according to grammatical order combined with context is designed. Finally, when the output verb result is inconsistent with the original text, it can automatically mark the error detection effect. The experimental results show that the algorithm model studied in this paper can effectively improve the detection accuracy and feedback efficiency and is more applicable and effective than the traditional manual detection method.

Highlights

With the rapid development of internationalization and globalization, English, as a global language, plays an important role in international trade, business cooperation, tourism, and other industries [1]
In order to propose a more reliable and accurate method, this study explores an automatic grammar error detection method based on recurrent neural network (RNN), and the research object is English verbs
With the rise of neural network research and the excellent development of information technology, English grammar error automatic recognition system with the function of evaluation and feedback is widely welcomed by English second language learners

Summary

Introduction

With the rapid development of internationalization and globalization, English, as a global language, plays an important role in international trade, business cooperation, tourism, and other industries [1]. According to the ASR technology used to realize GED, it is found that the results are mainly affected by two aspects: one is acoustic model (AM), and the other is language model (LM) [21] Based on the former, the research on deep neural network has improved the speech recognition rate [20]. Some people realized GED with the help of neural machine translation and applied statistical translation machine method and neural model [23] On this basis, in order to propose a more reliable and accurate method, this study explores an automatic grammar error detection method based on recurrent neural network (RNN), and the research object is English verbs

Automatic Detection of Grammatical Errors of English Verbs Based on RNN

Result

Findings

Conclusion