Evaluation of the Quality and Efficiency of English Translation of AI in Chinese Dance

Yunshu Bai; Yao Tong

doi:10.54254/2753-7048/2025.CB23804

Abstract

With the deep application of artificial intelligence technology in the field of translation. As an important carrier of traditional culture, the theory of Dance of China Dance has special requirements for machine translation due to its unique terminology system and aesthetic characteristics, it is urgent to establish a scientific evaluation system to examine the actual performance of existing AI translation systems in such texts. Taking an introduction to Chinese dance imagery as the research object, this study uses comparative analysis to evaluate the performance of ChatGPT and DeepSeek in the translation of professional dance texts. By constructing a four-dimensional evaluation system including language fluency, grammatical normalization, culturally-loaded word processing and original text fidelity. It is found that AI translation performs well at the level of basic language transfer. But at the same time, AI translation also presents such problems as simplification of cultural images, mistranslation of technical terms and loss of aesthetic features. Based on the empirical data, this study proposes the following suggestions to improve the quality of translation by building a professional terminology database and optimizing the context understanding algorithm.

Keywords: Artificial Intelligence , Chinese-English Translation , Dance of China , Cross-Cultural Communication , Chinese Traditional Culture

Article Information

Received: 4 June 2025

Published: 13 June 2025

DOI: https://doi.org/10.54254/2753-7048/2025.CB23804

Article Type: Research Article

Cite this article

Bai,Y.;Tong,Y. (2025). Evaluation of the Quality and Efficiency of English Translation of AI in Chinese Dance. Lecture Notes in Education Psychology and Public Media,94,45-49.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About this Volume

Volume Title: LNEP Vol.94

Part of Series: Lecture Notes in Education Psychology and Public Media

ISSN: 2753-7048 (Print) / 2753-7056 (Online)

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