SEMANTIC ADEQUACY IN POPULAR SCIENCE TEXTS FOR YOUNG AUDIENCES: A COMPARATIVE ANALYSIS OF GOOGLE TRANSLATE, DEEPL, CHATGPT AND MANUS AI TRANSLATIONS
Abstract
This study explores semantic adequacy in AI-based translations of popular science texts intended for young audiences. Translations produced by four systems are comparatively analyzed in terms of meaning accuracy, terminology, and completeness. The findings reveal differences in semantic performance and emphasize the importance of human supervision in ensuring reliable and precise translation.
References
Newmark, P. (1988). A Textbook of Translation. Prentice Hall.
2. Koehn, P. (2020). Neural Machine Translation. Cambridge University Press.
3. Frontiers for Young Minds. (n.d.). The fungi that fight bugs: Nature's tiny heroes.
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Copyright (c) 2026 Madina Zokirjonova
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