Issue |
SHS Web Conf.
Volume 199, 2024
2024 International Conference on Language Research and Communication (ICLRC 2024)
|
|
---|---|---|
Article Number | 01023 | |
Number of page(s) | 7 | |
Section | Language Academy and Education | |
DOI | https://doi.org/10.1051/shsconf/202419901023 | |
Published online | 23 October 2024 |
AI vs. human translation: Shaping the future of language learning through AI-generated bilingual captions
CW CHU College, Jiangsu Normal University, 221116 Xuzhou, China
* Corresponding author: 3020212366@jsnu.edu.cn
The impact of captions on language learning is one of the key research topics today. Researchers have found that the use of different types of captions will cause different learning effects on learners, and the order of using captions will also have different effects on language ability development. With the constant development of today’s artificial intelligence technology, however, there is still a research gap in the relevant issues of AI-generated captions. Therefore, this paper summarizes and analyzes the research related to artificial intelligence and captions and explores the relationship between AI-generated bilingual captions and English learners’ language learning. The study found that although AI-generated translation still has some shortcomings, its positive effect on English learners’ language learning is very obvious. Compared with manual translation, AI translation may be able to better mobilize learning enthusiasm and help ESP learning. In addition, teachers and learners are advised to use AI translation more flexibly and pay attention to some words that are easily mistranslated, such as cultural vocabulary and emerging vocabulary.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.