TYPES OF ERRORS IN AI TRANSLATION BETWEEN ENGLISH AND UZBEK: ANALYSIS AND CLASSIFICATION
Keywords:
artificial intelligence, neural machine translation, pragmatic equivalence, semantic error, contextual translation, linguistic analysisAbstract
This article provides an in-depth analysis of the types of errors that occur in artificial intelligence-based translation systems between English and Uzbek. The study systematically classifies lexical, grammatical, semantic, pragmatic, and cultural errors and explains their causes from linguistic and cognitive perspectives. The paper also examines the capabilities and limitations of neural machine translation systems. The findings indicate that although AI translation systems have approached formal accuracy, they still face challenges in ensuring pragmatic and cultural equivalence.
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Azerbaijan
Türkiye
Uzbekistan
Kazakhstan
Turkmenistan
Kyrgyzstan
Republic of Korea
Japan
India
United States of America
Kosovo