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

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Du, Haoyang, Chhatre, Kiran, Peters, Christopher, Keegan, Brian, McDonnell, Rachel, Ennis, Cathy
Natura: Preprint
Pubblicazione: 2025
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866912459470667776
author Du, Haoyang
Chhatre, Kiran
Peters, Christopher
Keegan, Brian
McDonnell, Rachel
Ennis, Cathy
author_facet Du, Haoyang
Chhatre, Kiran
Peters, Christopher
Keegan, Brian
McDonnell, Rachel
Ennis, Cathy
contents 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
format Preprint
id arxiv_https___arxiv_org_abs_2506_23777
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Synthetically Expressive: Evaluating gesture and voice for emotion and empathy in VR and 2D scenarios
Du, Haoyang
Chhatre, Kiran
Peters, Christopher
Keegan, Brian
McDonnell, Rachel
Ennis, Cathy
Graphics
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
title Synthetically Expressive: Evaluating gesture and voice for emotion and empathy in VR and 2D scenarios
topic Graphics
url https://arxiv.org/abs/2506.23777