Empathetic Conversational Agents: Utilizing Neural and Physiological Signals for Enhanced Empathetic Interactions

Résumé fourni par la source

Conversational agents (CAs) are transforming human-computer interaction, evolving from text-based chatbots to digital humans (DHs) capable of rich emotional expression. This study explores integrating neural and physiological signals into the perception module of CAs to enable real-time emotion detection and empathetic responses. We conducted a user study in which participants engaged with a DH about emotional topics. The DH mirrored participants’ emotions in real-time using neural and physiological cues. Results showed that users experienced stronger emotions and greater engagement during interactions with the Empathetic DH, highlighting the benefits of these signals for enhancing empathy. However, challenges remain, including recognition accuracy, emotional transition timing, individual differences, and limited voice modulation. Addressing these issues is key to advancing empathetic digital agents. This research demonstrates the promise of real-time physiological and neural emotion recognition for building emotionally intelligent CAs that foster deeper, more meaningful human-agent interactions.

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