Coordination of Speaking Opportunities in Virtual Reality: Analyzing Interaction Dynamics and Context-Aware Strategies

This study explores the factors influencing turn-taking coordination in virtual reality (VR) environments, with a focus on identifying key interaction dynamics that affect the ease of gaining speaking opportunities. By analyzing VR interaction data through logistic regression and clustering, we identify significant variables impacting turn-taking success and categorize typical interaction states that present unique coordination challenges. The findings reveal that features related to interaction proactivity, individual status, and communication quality significantly impact turn-taking outcomes. Furthermore, clustering analysis identifies five primary interaction contexts: high competition, intense interaction, prolonged single turn, high-status role, and low activity, each with unique turn-taking coordination requirements. This work provides insights into enhancing turn-taking support systems in VR, emphasizing contextually adaptive feedback to reduce speaking overlap and turn-taking failures, thereby improving overall interaction flow in immersive environments.

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Publication Details

Journal
Applied Sciences
Published
2024-12-23
DOI
https://doi.org/10.3390/app142412071
Primary Topic
Robotics and Automated Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Coordination of Speaking Opportunities in Virtual Reality: Analyzing Interaction Dynamics and Context-Aware Strategies

Chenghao Gu, Jiayi Zhang, Boxuan Ma, Shin’ichi Konomi et al.
Applied Sciences
Robotics and Automated Systems
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Coordination of Speaking Opportunities in Virtual Reality: Analyzing Interaction Dynamics and Context-Aware Strategies

Chenghao Gu, Jiayi Zhang, Boxuan Ma, Shin’ichi Konomi, Jiadong Chen, Zhankun Liu
article en

Abstract

This study explores the factors influencing turn-taking coordination in virtual reality (VR) environments, with a focus on identifying key interaction dynamics that affect the ease of gaining speaking opportunities. By analyzing VR interaction data through logistic regression and clustering, we identify significant variables impacting turn-taking success and categorize typical interaction states that present unique coordination challenges. The findings reveal that features related to interaction proactivity, individual status, and communication quality significantly impact turn-taking outcomes. Furthermore, clustering analysis identifies five primary interaction contexts: high competition, intense interaction, prolonged single turn, high-status role, and low activity, each with unique turn-taking coordination requirements. This work provides insights into enhancing turn-taking support systems in VR, emphasizing contextually adaptive feedback to reduce speaking overlap and turn-taking failures, thereby improving overall interaction flow in immersive environments.

Applied SciencesVol. 14(24)
Kyushu University (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 72%
Robotics and Automated Systems
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