This study introduces a novel system that integrates voice and facial recognition technologies to enhance human-computer interaction by accurately interpreting and responding to user emotions. Unlike conventional approaches that analyze either voice or facial expressions in isolation, this system combines both modalities, offering a more comprehensive understanding of emotional states. By evaluating facial expressions, vocal tones, and contextual conversation history, the system generates personalized, context-aware responses, fostering more natural and empathetic AI interactions. This advancement significantly improves user engagement and satisfaction, paving the way for emotionally intelligent AI applications across diverse fields.
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