Emotion-Aware Mental Health Chatbot: Leveraging Facial Expression Recognition and LLMs for Empathetic Support

Author(s)	Hetal Pandya, Amita Shah
Country	India
Abstract	This paper presents the design and development of an Emotion-Aware Mental Health Chatbot that leverages facial expression recognition (FER) and large language models (LLMs) to enable emotionally intelligent conversations. The system captures the user's real-time emotional state using webcam-based facial recognition, processes the data with a FER model, and integrates the detected emotion into the prompt for a LLaMA 2-based chatbot. The chatbot provides personalized, empathetic support to users in distress. The system is modular, efficient, and capable of running on modest hardware due to the use of quantized models. Through detailed testing and user feedback, the chatbot demonstrates potential as an accessible, scalable, and human-like mental health assistant suitable for deployment in educational, wellness, and remote counseling environments.
Keywords	Emotion Recognition, Mental Health Chatbot, Natural Language Processing, LLaMA 2, Empathetic AI, FER, Affective Computing
Published In	Volume 12, Issue 3, July-September 2021
Published On	2021-08-07

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