An Automatic Error Correction Method for English Composition Grammar Based on Multilayer Perceptron

Juan Wang, Feng Gu and Zaoli Yang

Mathematical Problems in Engineering, 2022, vol. 2022, 1-7

Abstract: In order to improve the timeliness of English grammar error correction and the recall rate of English grammar error correction, this paper proposes an automatic error correction method for English composition grammar based on a multilayer perceptron. On the basis of preprocessing the English composition corpus data, this paper extracts the grammatical features in the English composition corpus and constructs a grammatical feature set. We take the feature set as the input information of the multilayer perceptron and realize feature classification through network learning and training. The grammatical error items in the English composition are detected according to the similarity, and the error correction is completed by setting the penalty parameter and reducing the deviation parameter. The experimental results show that the syntax error detection time of this method is less than 6 minutes, the recall rate is higher than 90%, and the detection error rate is lower than 6%. The method improves the timeliness of grammatical error correction and improves the efficiency of error correction.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:6070445

DOI: 10.1155/2022/6070445

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