Linguistic and Cultural Fidelity in AI-Driven Translation: A Comparative Analysis of DeepL and Human Translations in English-Turkish Literary Short Stories

Authors : Mustafa Dolmacı

Pages : 92-109

Doi:10.63673/Lotus.1662868

View : 94 | Download : 58

Publication Date : 2025-06-24

Article Type : Research Paper

Abstract :This study investigates the differences between DeepL’s machine translations and human translations of English-to-Turkish fictional short stories, utilizing Katharina Reiss’ translation criticism model to analyze linguistic components. The study compares 381 sentences translated by DeepL with professional human translators from five literary works, identifying semantic, lexical, grammatical, stylistic, and nonsensical differences. Lexical differences are most common (33.86%), followed by semantic (22.05%), near-synonymous (20.73%), grammatical (9.16%), nonsensical (8.40%), and stylistic (5.77%). DeepL translated simple, straightforward words well but struggled with culturally nuanced expressions, figurative language, and contextual adjustments. While human translators utilized target-culture-focused procedures to retain literary aesthetics, DeepL used literal, source-text-focused methods, resulting in complex narrative incoherencies. The investigation found 32 incorrect DeepL translations, highlighting the need for literary post-editing. The results underscore DeepL\\\'s limitations in conveying stylistic nuances and cultural allusions, reinforcing the indispensable function of human translators in preserving the artistic and emotional richness of literary texts. This study evaluates AI-driven translation tools in literary contexts and recommends hybrid models that combine AI supported machine translation efficiency with human cultural and creative experience.
Keywords : makine çevirisi, insan çevirisi, kısa hikâye, dilsel bileşen

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