Comparing AI and Human Translation of O. Henry’s Short Stories under the Guidance of Functional Equivalence Theory

Thwe Nu San; Qingzheng Song; Changhui Bao

doi:10.54691/ybnn7923

Authors

Thwe Nu San
Qingzheng Song
Changhui Bao

DOI:

https://doi.org/10.54691/ybnn7923

Keywords:

Functional Equivalence Theory; AI translation; human translation; O. Henry’s short stories.

Abstract

Existing research has primarily focused on human translation, while analyses of AI translation remain relatively limited. To address this gap, this study employed Nida’s functional equivalence theory to compare the performance of AI translation and human translation in O. Henry’s short stories, analyzing their strengths and limitations. The study selected cases from the two translated versions of three O. Henry short stories. After conducting a qualitative comparison across three dimensions—linguistic, style, and readability—to assess the degree of functional equivalence, the study finds that AI translation is not a literal translation, but rather a flexibly-adjusted translation based on context and style. However, when translating complex texts, the translation can be stiff, and sometimes the style is too strong. In contrast, the human translation is overall logical, coherent and natural with more stable translation quality. However, human translation may cost more time and thus is not as efficient as AI translation. This study validates the applicability of functional equivalence theory in literary translation and provides implications for optimizing AI translation, contributing to further explorations of effective human-machine collaborative translation models.

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