Online Translation Teaching System Based on Artificial Intelligence

Online Translation Teaching System Based on Artificial Intelligence | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 25 January 2025 V1 Latest version Share on Online Translation Teaching System Based on Artificial Intelligence Authors : Zheng Li 0009-0005-7742-4594 [email protected] , Lei Fei , and Minmin Ye Authors Info & Affiliations https://doi.org/10.22541/au.173779415.57882736/v1 206 views 45 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract This study explores the development and implementation of an AI-based online translation teaching system with a layered architecture, including data, foundation, business, and user layers. The data layer integrates SQL and NoSQL databases for efficient storage and querying of various data types. The foundation layer combines system management with intelligent services, utilizing large models and multimodal technologies to enhance teaching efficiency, support blended learning, and drive the digital transformation of resources. The business layer supports four key platforms---translation teaching, training, self-learning, and testing---along with an intelligent terminal service platform. The user layer, with four interfaces based on participant roles, ensures smooth system operation. A microservices architecture improves stability and resource utilization. Built on the Langchain framework, the intelligent foundation has been tested for reliability and performance, and the terminal service can handle multiple concurrent connections and process students' audio data accurately. Supplementary Material File (online_translation_teaching_system_based_on_artificial_intelligence.docx(revised_one).docx) Download 595.75 KB Information & Authors Information Version history V1 Version 1 25 January 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords artificial intelligence layered architecture online translation teaching system Authors Affiliations Zheng Li 0009-0005-7742-4594 [email protected] Anhui University of Science and Technology School of Foreign Languages View all articles by this author Lei Fei Anhui University of Science and Technology School of Foreign Languages View all articles by this author Minmin Ye Anhui University of Science and Technology School of Foreign Languages View all articles by this author Metrics & Citations Metrics Article Usage 206 views 45 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Zheng Li, Lei Fei, Minmin Ye. Online Translation Teaching System Based on Artificial Intelligence. Authorea . 25 January 2025. DOI: https://doi.org/10.22541/au.173779415.57882736/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. 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