Developing Social Robots with Empathetic Non-Verbal Cues Using Large Language Models

Understand

We propose augmenting the empathetic capacities of social robots by integrating non-verbal cues.

• Our primary contribution is the design and labeling of four types of empathetic non-verbal cues, abbreviated as SAFE: Speech, Action (gesture), Facial expression, and Emotion, in a social robot.
• These cues are generated using a Large Language Model (LLM).
• We developed an LLM-based conversational system for the robot and assessed its alignment with social cues as defined by human counselors.