Proceedings of the 2023 7th International Seminar on Education, Management and Social Sciences (ISEMSS 2023)

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Investigation on the Application of Artificial Intelligence Large Language Model in Translation Tasks

Authors
Chunlan Jiang1, *
1Senior Translation School, Xi’an Fanyi University, Shaanxi, Xi’an, China, 710105
*Corresponding author. Email: jiangchunlanzhengf@126.com
Corresponding Author
Chunlan Jiang
Available Online 31 October 2023.
DOI
10.2991/978-2-38476-126-5_147How to use a DOI?
Keywords
Artificial Intelligence; Natural Language Processing; Recurrent Neural Network; Large Language Model
Abstract

As an emerging language technology, the application of Artificial Intelligence (AI) Large Language Model (LLM) in translation tasks has an important background. Based on a large number of experimental data, this paper compared traditional machine translation and Google translate, and evaluated the performance of AI LLM in multilingual translation tasks. The experimental results showed that compared with traditional machine translation and Google translate, the AI LLM performed better in terms of translation quality and speed. Specifically, the Bilingual Evaluation Understudy (BLEU) score of the LLM was about 5 percentage points higher than that of traditional machine translation and Google translate, and the BLEU value per second was about 5 percentage points higher than that of traditional machine translation; in terms of speed, the LLM was 13.53 seconds faster than traditional machine translation on average. These findings indicated that the AI LLM had broad application prospects and important application value in practical applications, and could provide better technical support for achieving language translation.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 7th International Seminar on Education, Management and Social Sciences (ISEMSS 2023)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
31 October 2023
ISBN
10.2991/978-2-38476-126-5_147
ISSN
2352-5398
DOI
10.2991/978-2-38476-126-5_147How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Chunlan Jiang
PY  - 2023
DA  - 2023/10/31
TI  - Investigation on the Application of Artificial Intelligence Large Language Model in Translation Tasks
BT  - Proceedings of the 2023 7th International Seminar on Education, Management and Social Sciences (ISEMSS 2023)
PB  - Atlantis Press
SP  - 1341
EP  - 1351
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-126-5_147
DO  - 10.2991/978-2-38476-126-5_147
ID  - Jiang2023
ER  -