Title: Study on machine English translation error identification based on naive Bayesian algorithm

Authors: Zhongping Yao

Addresses: School of Foreign Languages, Jiujiang University, Jiangxi, Jiujiang 332005, China

Abstract: In order to improve the effect and accuracy of machine English translation error identification and shorten the time of machine English translation error identification, a machine English translation error identification method based on naive Bayesian algorithm is proposed. Naive Bayesian algorithm is used to extract the information features of machine English translation. Combined with the automatic translation evaluation method, the results of machine English translation are judged. According to the judgment results, the maximum entropy classifier is selected to identify the error types of machine English translation information, so as to realise the error identification of machine English translation. The experimental results show that the proposed method has a good effect on machine English translation error identification, can effectively improve the accuracy of machine English translation error identification and shorten the time of machine English translation error identification.

Keywords: naive Bayesian algorithm; maximum entropy classifier; automatic translation evaluation; machine English translation; translation error identification.

DOI: 10.1504/IJRIS.2023.136364

International Journal of Reasoning-based Intelligent Systems, 2023 Vol.15 No.3/4, pp.277 - 283

Received: 16 Mar 2022
Accepted: 12 Oct 2022
Published online: 31 Jan 2024 *

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