LEXICAL-SEMANTIC DIFFERENTIATION OF SYNONYMS IN TURKIC LANGUAGES: AN AI AND PARALLEL CORPUS-BASED APPROACH TO TRANSLATOR TRAINING
Keywords:
synonymy, lexical-semantic differentiation of action verbs, parallel corpora, artificial intelligence, translator training, translation studies; collocational behavior; semantic nuanceAbstract
Despite extensive research on synonymy in linguistics, the problem of accurate synonym selection in translation remains unresolved, particularly in Turkic languages where subtle lexical-semantic distinctions significantly affect meaning and stylistic adequacy. This paper proposes an AI-supported, parallel corpus-based approach to teaching synonym usage differentiation for translator training. Drawing on Uzbek–English parallel texts, the study demonstrates how corpus evidence, combined with AI-assisted analysis, can reveal fine-grained distinctions between synonymous units, especially within action verbs. The findings suggest that integrating parallel corpora and artificial intelligence tools into translator education enhances learners’ ability to identify contextual, stylistic, and semantic nuances of synonyms, thereby improving translation quality. The paper contributes both a methodological framework and pedagogical implications for adapting Turkic languages to modern language technologies.
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