Effectiveness Of Ai-Based Contextual And Culturally Adaptive Translation Models And Their Linguistic Analysis

Abstract

This article analyzes the effectiveness of AI-based contextual and culturally adaptive translation models from a linguistic perspective. The study examines the ability of modern AI translation systems to process context, polysemy and culture-specific units. Using Uzbek culture-bound words such as “mahalla”, “palov” and “toy” as examples, the paper demonstrates typical semantic and pragmatic difficulties of automatic translation. It is argued that despite the high level of formal accuracy, AI translation still requires linguistic and cultural supervision and should be regarded as a supportive rather than fully autonomous tool.