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June 3, 20260 citationsOpen Access

AI-Assisted Translation and the Preservation of National Colour in Literary Texts

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ZXZarrina Shadiyarovna Xasanova

Key Points

  • This study aims to evaluate AI-assisted translation's ability to maintain national colour in literary texts.
  • Employs comparative, descriptive, and qualitative methods.
  • Analyzes culture-specific units in Uzbek literary texts and their English translations.
  • Compares the effectiveness of machine-generated translations with human translation strategies.
  • AI systems achieve high lexical and grammatical accuracy.
  • Machine translations frequently miss cultural nuances and implicit meanings.
  • Successful literary translation requires combining AI tools with human cultural insights.

Abstract

The rapid development of artificial intelligence technologies has significantly transformed contemporary translation practices. AI-powered translation systems have demonstrated remarkable efficiency in processing large volumes of text; however, challenges remain regarding the preservation of national colour in literary translation. National colour encompasses culture-specific elements, historical references, traditions, customs, and linguistic features that reflect a nation’s identity. This study investigates the effectiveness of AI-assisted translation in preserving national colour in literary texts and compares machine-generated translations with human translation strategies. The research employs comparative, descriptive, and qualitative methods to analyze culture-specific units found in Uzbek literary texts and their English translations. The findings reveal that although AI systems achieve high levels of lexical and grammatical accuracy, they often fail to convey cultural nuances, implicit meanings, and national identity embedded in literary discourse. The study argues that successful literary translation requires a combination of artificial intelligence tools and human cultural competence. The results contribute to translation studies, comparative linguistics, and the growing field of AI-assisted language technologies.

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Cite This Study

Zarrina Shadiyarovna Xasanova (2026) studied this question.

synapsesocial.com/papers/6a1fc730dee9eb8c0dce80adhttps://doi.org/10.5281/zenodo.20484636
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