Can the three-level analysis of language use be applied in human-machine collaborative translation with ChatGPT? - A case study of culturally loaded words in Thai translation

Qin Qin, Jiaqiao Zhu, Xingyu Yao, Min Le, Yuwen Yang, Junlanzeng and Xinhui Lu

Abstract

           This study explores the application of the Three-Level Analysis of Language Use (Xu & Liu, 2024) in human-machine collaborative translation of culture-loaded words. By examining the translation of terms such as xietian and sheguang, the study analyzes the effectiveness of the three-level analysis in enhancing translation accuracy and cultural adaptability. The first-level analysis focuses on literal translation, the second-level analysis integrates contextual background for refinement, and the third-level analysis delves into cultural and academic significance to ensure the transmission of deep cultural connotations. Findings indicate that the combination of human translators' in-depth understanding with ChatGPT’s efficiency significantly improves translation quality, particularly for complex terms involving cultural and historical contexts. This approach provides new insights into human-machine collaborative translation and highlights its potential in handling culture-loaded words.

 

Keyword : Three-Level Analysis of Language Use, Human-Machine Collaborative Translation, Culture-Loaded Words

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