EVALUATION OF MACHINE TRANSLATION IN CENTRAL ASIA: CURRENT CHALLENGES AND EMERGING SOLUTIONS

Abstract

Machine Translation (MT) has rapidly advanced in recent years, driven by developments in neural networks and large-scale datasets. However, these advancements have been unevenly applied across languages, with limited focus on the complex linguistic diversity of Central Asia. This study evaluates MT performance for Central Asian languages—Kazakh, Kyrgyz, Uzbek, Tajik, and Turkmen—and identifies key obstacles to achieving accurate and contextually appropriate translations.