AI system specifically designed to interpret and analyse visual biometric signals

Emotions play a vital role in human interactions, yet accurately assessing them remains a challenge. This project aims to enhance emotion recognition by integrating advanced eye-tracking algorithms, microfacial expression analysis, and speech-based emotion detection.By refining eye-tracking technology, we can capture subtle gaze patterns that reveal cognitive engagement. When combined with microfacial expressions—brief, involuntary facial cues—we gain deeper insight into genuine emotional states. Integrating speech and voice tone analysis further strengthens this multimodal approach, providing a comprehensive understanding of emotions, particularly in clinical and therapeutic settings. Additionally, generative AI will be used to simulate emotional states and study behavioral patterns across diverse demographics. These AI-driven insights will improve cognitive state modeling, enabling personalized interventions and real-time treatment optimization This research has wide-ranging applications, from mental health diagnostics to human-computer interaction, paving the way for AI systems that can recognize and respond to human emotions with greater accuracy and empathy.