Published Paper Details:

Chatbots are key tools for intelligent communication, offering real-time, automated responses across various domains. This paper introduces a Python-based, voice-enabled chatbot tailored for academic environments. It supports both speech and text input/output, using natural language processing (NLP), speech recognition, and text-to-speech (TTS) to handle user queries effectively. The system utilizes a structured JSON knowledge base to provide quick, context-aware responses on topics such as admissions, courses, and facilities. Built with libraries such as speech recognition, pyttsx3, and json, it ensures smooth, intuitive interaction without complex navigation. Notably, the chatbot operates offline, making it suitable for areas with low connectivity. Its modular design also supports future enhancements, including sentiment analysis, multilingual features, and cloud integration. This paper highlights how AI-driven voice interfaces can enhance human-computer interaction, streamline academic support, and improve access to institutional information.