Machine translation in Uzbekistan: challenges, advances, and future directions

Machine Translation (MT) has made significant strides globally, yet for low-resource languages like Uzbek, challenges remain. Despite the advances in neural machine translation (NMT) and deep learning, language-specific challenges such as data scarcity, syntactic complexity, and morphological richness continue to hinder progress. This paper reviews the development and application of MT in Uzbekistan, examining the contributions of Uzbek scientists and international researchers. This article analyzes the state of MT, highlight the challenges specific to Uzbek, and suggest directions for future research, focusing on corpus building, neural models, and evaluation metrics.