Cargando…

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

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 learni...

Descripción completa

Detalles Bibliográficos
Autores principales: Liu, Yutong, Zhang, Shile
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9977533/
https://www.ncbi.nlm.nih.gov/pubmed/36873384
http://dx.doi.org/10.1155/2023/9450816
_version_ 1784899312482779136
author Liu, Yutong
Zhang, Shile
author_facet Liu, Yutong
Zhang, Shile
author_sort Liu, Yutong
collection PubMed
description 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.
format Online
Article
Text
id pubmed-9977533
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-99775332023-03-02 Design and Proofreading of the English-Chinese Computer-Aided Translation System by the Neural Network Liu, Yutong Zhang, Shile Comput Intell Neurosci Research Article 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. Hindawi 2023-02-22 /pmc/articles/PMC9977533/ /pubmed/36873384 http://dx.doi.org/10.1155/2023/9450816 Text en Copyright © 2023 Yutong Liu and Shile Zhang. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Liu, Yutong
Zhang, Shile
Design and Proofreading of the English-Chinese Computer-Aided Translation System by the Neural Network
title Design and Proofreading of the English-Chinese Computer-Aided Translation System by the Neural Network
title_full Design and Proofreading of the English-Chinese Computer-Aided Translation System by the Neural Network
title_fullStr Design and Proofreading of the English-Chinese Computer-Aided Translation System by the Neural Network
title_full_unstemmed Design and Proofreading of the English-Chinese Computer-Aided Translation System by the Neural Network
title_short Design and Proofreading of the English-Chinese Computer-Aided Translation System by the Neural Network
title_sort design and proofreading of the english-chinese computer-aided translation system by the neural network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9977533/
https://www.ncbi.nlm.nih.gov/pubmed/36873384
http://dx.doi.org/10.1155/2023/9450816
work_keys_str_mv AT liuyutong designandproofreadingoftheenglishchinesecomputeraidedtranslationsystembytheneuralnetwork
AT zhangshile designandproofreadingoftheenglishchinesecomputeraidedtranslationsystembytheneuralnetwork