Trust in Virtual Agents: Exploring the Role of Stylization and Voice

With the continuous advancement of artificial intelligence technology, data-driven methods for reconstructing and animating virtual agents have achieved increasing levels of realism. However, there is limited research on how these novel data-driven methods, combined with voice cues, affect user perceptions. We use advanced data-driven methods to reconstruct stylized agents and combine them with synthesized voices to study their effects on users' trust and other perceptions (e.g. social presence and empathy). Through an experiment with 27 participants, our findings reveal that stylized virtual agents enhance user trust to a degree comparable to real style, while voice has a negligible effect on trust. Additionally, elder agents are more likely to be trusted. The style of the agents also plays a key role in participants' perceived realism, and audio-visual matching significantly enhances perceived empathy. These results provide new insights into designing trustworthy virtual agents and further support and validate the audio-visual integration theory.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Visualization and Computer Graphics
Published
2025-03-11
DOI
https://doi.org/10.1109/tvcg.2025.3549566
Citations
9
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
22.33
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Trust in Virtual Agents: Exploring the Role of Stylization and Voice

Honglei Guo, Fariba Mostajeran, Tao Yu, Yang Gao et al.
9 citations
IEEE Transactions on Visualization and Computer Graphics
Natural Language Processing Techniques
22.33
article

Trust in Virtual Agents: Exploring the Role of Stylization and Voice

Honglei Guo, Fariba Mostajeran, Tao Yu, Yang Gao, Guangtao Zhang, Yangbin Dai, Binge Zheng
article en
9 citations

Abstract

With the continuous advancement of artificial intelligence technology, data-driven methods for reconstructing and animating virtual agents have achieved increasing levels of realism. However, there is limited research on how these novel data-driven methods, combined with voice cues, affect user perceptions. We use advanced data-driven methods to reconstruct stylized agents and combine them with synthesized voices to study their effects on users' trust and other perceptions (e.g. social presence and empathy). Through an experiment with 27 participants, our findings reveal that stylized virtual agents enhance user trust to a degree comparable to real style, while voice has a negligible effect on trust. Additionally, elder agents are more likely to be trusted. The style of the agents also plays a key role in participants' perceived realism, and audio-visual matching significantly enhances perceived empathy. These results provide new insights into designing trustworthy virtual agents and further support and validate the audio-visual integration theory.

IEEE Transactions on Visualization and Computer GraphicsVol. 31(5)
Universität Hamburg (DE), Beihang University (CN), Tsinghua University (CN)
Openalex Percentile: Top 1%
Natural Language Processing Techniques
22.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.