Design and Proofreading of the English-Chinese Computer-Aided Translation System by the Neural Network

Author:

Liu Yutong1ORCID,Zhang Shile2

Affiliation:

1. School of Humanities and Social Sciences, Xi’an Polytechnic University, Xi’an City 710048, China

2. Shaanxi Contemporary Red Culture Training and Education Center, Xi’an City 710061, China

Abstract

At present, complete machine translation (MT) cannot meet the needs of information communication and cultural exchange, and the speed of complete human translation is too slow. Therefore, if MT is used to assist in the process of English-Chinese translation, it can not only prove that machine learning (ML) can translate English to Chinese but also improve the translation efficiency and accuracy of translators through human-machine cooperation. The research on the mutual cooperation between ML and human translation has an important research significance for translation systems. An English-Chinese computer-aided translation (CAT) system is designed and proofread based on a neural network (NN) model. First, it gives a brief overview of CAT. Second, the related theory of the NN model is discussed. An English-Chinese CAT and proofreading system based on the recurrent neural network (RNN) is constructed. Finally, the translation accuracy and proofreading recognition rate of the translation files of 17 different projects under different models are studied and analyzed. The research results reveal that according to the different translation properties of different texts, the average accuracy rate of text translation under the RNN model is 93.96%, and the mean accuracy of text translation under the transformer model is 90.60%. The translation accuracy of the RNN model in the CAT system is 3.36% higher than that of the transformer model. The English-Chinese CAT system based on the RNN model has different proofreading results for sentence processing, sentence alignment, and inconsistency detection of translation files of different projects. Among them, the recognition rate for sentence alignment and the inconsistency detection of English-Chinese translation is high, and the expected effect is achieved. The design of the English-Chinese CAT and proofreading system based on the RNN can make the translation and proofreading be carried out simultaneously, which greatly improves the efficiency of translation work. Meanwhile, the above research methods can improve the problems encountered in the current English-Chinese translation, provide a path for the bilingual translation process, and have certain promotion prospects.

Publisher

Hindawi Limited

Subject

General Mathematics,General Medicine,General Neuroscience,General Computer Science

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Study on Lexical Disambiguation in English Translation Based on Twin Neural Networks;Applied Mathematics and Nonlinear Sciences;2024-01-01

2. Exploring English Translation Strategies Oriented by Big Data Technology;Applied Mathematics and Nonlinear Sciences;2024-01-01

3. Research on Intelligent English to Chinese Translation Based on Transformer Model;2023 IEEE 11th Joint International Information Technology and Artificial Intelligence Conference (ITAIC);2023-12-08

4. Retracted: Design and Proofreading of the English-Chinese Computer-Aided Translation System by the Neural Network;Computational Intelligence and Neuroscience;2023-10-04

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