Cross-Language Translation Evaluation: A Comparative Analysis of the Quality of English-Chinese Interpretation by AI Models and Strategies for Improvement

Tong Su

doi:10.63313/LLCS.9057

Authors

Tong Su Hangzhou Normal University of Foreign Languages, Hangzhou 311121, China Author

DOI:

https://doi.org/10.63313/LLCS.9057

Keywords:

AI Models, English-Chinese Translation, BLEU Model, Translation Quality, English-Chinese Comparison

Abstract

Machine translation, as one of the important functions of artificial intelligence, plays an increasingly important role in cross-linguistic communication. The paper is meant to evaluate the performance of domestic up-and-coming AI models in English-Chinese mutual translation tasks in order to analyze their functions and effects comparatively and explore strategies to improve the quality of AI translation in the process of both 2 languages. Based on the literature review in the first section, we put forward the hypothesis that there are certain deficiencies in AI translation tasks, and that different types of errors will be produced depending on the target language. We will use both quantitative and qualitative analysis methods, combined with example analysis and the application of the BLEU model, to evaluate the AI translation output in terms of several dimensions. We also point out the limitations of the study and discuss the main problems of AI translation and propose targeted enhancement strategies in the conclusion part.

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