AI-Powered Digital Twin Professor for Interactive Teaching and Q&A using Open-Source Technologies

With the rapid advancement of Artificial Intelligence, there is an increasing need to preserve, scale, and personalize human expertise in the field of education.The project titled "AI Twin for Professors" aims to develop a digital, AI-powered replica of a professor that can interact with students through text, voice, and visual responses, closely simulating a real classroom teaching experience.The system is designed using a structured four-module architecture to ensure balanced workload distribution and effective collaboration among team members.The first module focuses on building a robust knowledge base by collecting lecture materials, converting audio content into text using Whisper, preprocessing the data, and generating vector embeddings using LangChain and ChromaDB to enable accurate and context-aware question answering.The second module develops a speech system with voice cloning capabilities, allowing the AI twin to respond in the professor's voice while supporting multilingual interaction through speech-to-text and text-to-speech pipelines.The third module handles the visual interface by generating an animated avatar of the professor using face animation and lip-sync technologies for realistic video responses.The fourth module integrates all components into a unified web application using modern frontend and backend technologies.The proposed system ensures 24×7 availability, personalized learning support, and incorporates ethical safeguards such as consent and watermarking.Overall, the project demonstrates effective integration of NLP, speech processing, computer vision, and web technologies to create an intelligent and ethical AI-based educational assistant.