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The Bangla dialect speech to Standard English translation system for rural telemedicine applications is a collaborative platform to enhance global medical support. Healthcare in Bangladesh is less advanced than in developed countries, and this study aims to assist patients deprived of proper treatment and medical credibility. According to the Global Health Security Index (GHS 2019), Bangladesh ranks 132nd in overall public health risk, 124th in norms, and 147th in response, highlighting significant challenges in the healthcare sector. Access to dependable healthcare services is limited, and high copayments and travel costs further restrict access to top notch healthcare abroad. To address these crucial issues in rural telemedicine, we propose a system to improve the accuracy of medical consultations through speech translation. Linguistic barriers due to diverse dialects across Bangladesh hinder effective communication between rural residents and foreign medical practitioners. The country’s rich linguistic heritage, with its dialects varying in phonetics, fluency, rhythm, prosody, and sociolinguistic influences, presents significant challenges in dialect identification. Our study introduces a groundbreaking speech translation system that revolutionizes how we overcome these challenges. The system is ingeniously designed to convert dialects into Standard Bangla and seamlessly integrate real-time English speech translation for global medical support. It harnesses the power of state-of-the-art models to achieve unparalleled accuracy in real-time translation from various local Bangla dialects to English. We use encompass prominent Large Language Models such as mBERT, and T5; Neural Machine Translation like NMT5; and Recurrent Neural Network (RNN) Models such as GRU, BARK, and Bi-Directional LSTM to achieve unparalleled accuracy in real-time translation from various local Bangla dialects to English. This research addresses linguistic barriers in rural settings and significantly enhances cross linguistic medical consultations. The system is seamlessly integrated with popular telemedicine platforms such as [specific platforms], making it practical and easy to implement in real world scenarios.