Mental Health Companion for Trauma Recovery Using Multi-Modal Emotion Recognition

This paper presents a mental health companion designed to assist students experiencing trauma-induced emotional distress. Using multi-modal emotion recognition, the system integrates speech, facial expressions, and body posture data to provide real-time coping strategies. Our approach enhances accuracy, reduces latency, and improves user satisfaction, making it a valuable tool for trauma recovery and emotional regulation.