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Sensing the Intentions to Speak in VR Group Discussions.
Chen, Jiadong; Gu, Chenghao; Zhang, Jiayi; Liu, Zhankun; Konomi, Shin'ichi.
Afiliação
  • Chen J; Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan.
  • Gu C; Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan.
  • Zhang J; Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan.
  • Liu Z; Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan.
  • Konomi S; Faculty of Arts and Science, Kyushu University, Fukuoka 819-0395, Japan.
Sensors (Basel) ; 24(2)2024 Jan 07.
Article em En | MEDLINE | ID: mdl-38257455
ABSTRACT
While virtual reality (VR) technologies enable remote communication through the use of 3D avatars, it is often difficult to foster engaging group discussions without addressing the limitations to the non-verbal communication among distributed participants. In this paper, we discuss a technique to detect the intentions to speak in group discussions by tapping into intricate sensor data streams from VR headsets and hand-controllers. To this end, we developed a prototype VR group discussion app equipped with comprehensive sensor data-logging functions and conducted an experiment of VR group discussions (N = 24). We used the quantitative and qualitative experimental data to analyze participants' experiences of group discussions in relation to the temporal patterns of their different speaking intentions. We then propose a sensor-based mechanism for detecting speaking intentions by employing a sampling strategy that considers the temporal patterns of speaking intentions, and we verify the feasibility of our approach in group discussion settings.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Qualitative_research Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Qualitative_research Idioma: En Ano de publicação: 2024 Tipo de documento: Article