AI-Powered Language Translation for Low-Resource Languages

This paper presents a comprehensive technical framework for AI-powered language translation tailored specifically for low-resource languages. Our approach addresses the severe data scarcity issues by integrating transfer learning, multilingual pre-training, and domain adaptation into a unified neural machine translation (NMT) architecture. We mathematically formalize the translation process as a probabilistic sequence-to-sequence problem, expressed as