CULTURAL-CONNOTATIVE FEATURES OF PHRASEOLOGICAL UNITS IN DIFFERENT LANGUAGES AND THEIR INTERPRETATION THROUGH ARTIFICIAL INTELLIGENCE

Authors

  • Shukurova Yulduz Yaxshimurotovna Department of Foreign Language and Social Sciences, Asia International University, English Teacher Bukhara, Uzbekistan

DOI:

https://doi.org/10.55640/

Keywords:

Phraseological units, cultural connotation, cross-cultural semantics, idiom translation, artificial intelligence, semantic interpretation, machine translation, multilingual NLP.

Abstract

This article examines the cultural and connotative characteristics of phraseological units across English, Uzbek, Russian, and other languages. Drawing on the findings of scholars such as Djumaeva, Nasirova, Niyadullayeva, Mahmudova, and Goziyeva, the study provides an integrated analysis of the linguistic and cultural challenges associated with the translation of idioms. Furthermore, the paper proposes a unified AI-based methodological framework for detecting, interpreting, and translating phraseological units while preserving their semantic depth and cultural specificity. The study also outlines a five-stage computational model based on linguistic corpora, semantic embedding, context-sensitive neural architectures, and post-editing mechanisms aimed at improving the automatic interpretation of idioms in machine translation systems.

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References

1. Djumaeva, G. (2023). Comparative Study of Idioms in English and Uzbek Languages.

2. Nasirova, K. (2022). Idiomatic Expressions and Cultural Values in Multilingual Context.

3. Niyadullayeva, S. (2023). Translating Idioms and Proverbs Across Cultures.

4. Mahmudova, F. (2021). Linguistic and Cultural Features of Phraseological Units.

5. Goziyeva, M. (2022). Semantic Classification of Animal-based Idioms in English and Uzbek.

7. Sharipova, O. (2021). Phytonymic Phraseological Units: Linguistic and Cultural Analysis.

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Published

2025-12-10

How to Cite

CULTURAL-CONNOTATIVE FEATURES OF PHRASEOLOGICAL UNITS IN DIFFERENT LANGUAGES AND THEIR INTERPRETATION THROUGH ARTIFICIAL INTELLIGENCE. (2025). Journal of Multidisciplinary Sciences and Innovations, 4(11), 953-954. https://doi.org/10.55640/

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