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Deep learning based optical network transmission application in Chinese English translation system in cloud computing environment

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Abstract

At present, human translation is characterized by low efficiency, high cost, high consumption of resources and time, so it is urgent to study automatic translation technology to meet the needs of information interaction and language communication in various countries under the background of economic globalization. In order to improve the performance of Chinese-English translation system, this study aims to use optical network transmission technology to optimize the translation process. This research is based on deep learning model and uses optical network transmission technology to implement Chinese-English translation system. The neural network model is used to train the Chinese-English translation, and then the data is transmitted to the cloud for translation using optical network transmission technology. Finally, the translation result is returned to the user. The system can learn by itself on the basis of analyzing source documents, and predict target translation output by extracting features. The system is equipped with a translation engine based on the data source, which can realize interactive translation, and the final output can be achieved by processing the predicted translation output and based on the translator’s understanding. Through the design of simulation experiments for system detection, the results show that the Chinese English translation model system has a high translation quality. By comparing it with the baseline system, it can be seen that both of them can translate sentences normally in 8 PR cycles (PR * 8, about 18% KSMR), and the data set improvement rate is about + 35 BLEU, that is, 76 BLEU is finally achieved. This proves that users can maintain the translation accuracy while reducing the number of effective interactions by using the optimized translation model to translate the target text, showing the effectiveness. In this paper, an interactive Chinese English translation system is designed by combining deep learning with cloud computing.

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Funding

This paper was supported by (1) 2022 Humanities and Social Sciences Project of China Ministry of Education: Research on the Construction of International Image and External Communication Strategies in the Guangdong-Hong Kong-Macao Greater Bay Area, Project Approval Number:22YJCZH250; (2) 2021 Quality Engineering Project of Guangzhou College of Commerce–Higher Education Teaching Reform Project (Project Title: Exploration and Practice of English for Computer Purposes Wisdom Teaching Model Based on INSPIRE Model), Project Approval Number: 2021JXGG13.

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Authors and Affiliations

  1. School of Foreign Languages, Guangzhou College of Commerce, Guangzhou, 511363, Guangdong, China

    Yinghong Mai & Xin Yuan

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  1. Yinghong Mai
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  2. Xin Yuan
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Yinghong Mai has done the first version, Xin Yuan has done the simulations. All authors have contributed to the paper’s analysis, discussion, writing, and revision.

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Correspondence to Xin Yuan.

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Mai, Y., Yuan, X. Deep learning based optical network transmission application in Chinese English translation system in cloud computing environment. Opt Quant Electron 56, 598 (2024). https://doi.org/10.1007/s11082-024-06297-8

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