International Journal of Scientific Research and Engineering Development

Good communication between doctors and patients is essential for good quality healthcare service. Unfortunately, factors such as time pressures, the use of medical jargon, and emotional stress often impact patients' comprehension and ratability. This paper outlines the development of "CareVoice AI" an emotionaware consultation system comprised of six single integrated AI models, the Goal is to enhance empathy, comprehension, and collaboration in health care communication: 1) Adaptive Empathy Chatbot (AEC), 2) Contextual Memory Assistant (CMA), 3) Cooperative Virtual Assistant (CVA), 4) Emotion-Sensitive Voice Recognition (ESVR), 5) Dynamic Voice-to-Meaning Translator (DVMT), and 6) Multilingual Accessibility Voice Assistant (MAVA). Collectively, these models develop a multimodal communication bridge between patients and physicians. The architecture envisioned conceptually with NLP, speech recognition, and sentiment analysis frameworks has the potential to foster doctor-patient conversation, ease physician workload, and increase equitable, empathetic care.