THE IMPACT OF ARTIFICIAL INTELLIGENCE IN COMPARATIVE LINGUISTICS: A COMPARATIVE ANALYSIS OF SYNTACTIC AND SEMANTIC ERRORS IN MACHINE TRANSLATION OF TURKIC LANGUAGES

Abstract

This article explores an under examined topic in comparative linguistics: the syntactic and semantic errors in machine translation systems for Turkic languages, focusing on Uzbek and Turkish. Using platforms like Google Translate and Microsoft Translator, the study analyzes translation errors to highlight differences between Central Asian and Anatolian Turkic variants. Grounded in recent advancements in natural language processing (NLP), this research proposes new insights for comparative linguistics and underscores the need for specialized corpora for Turkic languages. The findings aim to contribute to both NLP and linguistic scholarship by identifying AI limitations and suggesting improvements.