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arXiv · 2506.23777

Synthetically Expressive: Evaluating gesture and voice for emotion and empathy in VR and 2D scenarios

Haoyang Du·Kiran Chhatre·Christopher Peters·Brian Keegan·Rachel McDonnell·Cathy Ennis
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Abstract

The creation of virtual humans increasingly leverages automated synthesis of speech and gestures, enabling expressive, adaptable agents that effectively engage users. However, the independent development of voice and gesture generation technologies, alongside the growing popularity of virtual reality (VR), presents significant questions about the integration of these signals and their ability to convey emotional detail in immersive environments. In this paper, we evaluate the influence of real and synthetic gestures and speech, alongside varying levels of immersion (VR vs. 2D displays) and emotional contexts (positive, neutral, negative) on user perceptions. We investigate how immersion affects the perceived match between gestures and speech and the impact on key aspects of user experience, including emotional and empathetic responses and the sense of co-presence. Our findings indicate that while VR enhances the perception of natural gesture-voice pairings, it does not similarly improve synthetic ones - amplifying the perceptual gap between them. These results highlight the need to reassess gesture appropriateness and refine AI-driven synthesis for immersive environments. Supplementary video: https://youtu.be/WMfjIB1X-dc

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Haoyang Du, Kiran Chhatre, Christopher Peters, Brian Keegan, Rachel McDonnell, Cathy Ennis. 2025-06-30. Synthetically Expressive: Evaluating gesture and voice for emotion and empathy in VR and 2D scenarios. https://arxiv.org/abs/2506.23777

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