Work

Voices Unveiled: Quality of Experience in Collaborative VR via AssemblyAI and NASA-TLX Analysis

Year: 2024

Type: conference-paper

Abstract: In order to understand the sentiments between users as they worked together as part of a collaborative Virtual Reality (VR) task, this research analyzed voice interaction using Assembly AI. The real-time conversations between 11 pairs of users were captured as they performed a joint puzzle task. The users were in separate physical spaces but connected in a shared virtual setting. The extracted voice sentiments were correlated with self-reported frustration levels and task completion times. The findings reveal a significant positive correlation between negative sentiments and frustration (r=0.73, p≤0.05) and a negative correlation between positive sentiments and task completion time (r=-0.87, p≤0.001). This shows the relationship between sentiment (positive and negative) and task completion in collaborative VR. These results highlight the potential benefits of analyzing voice sentiment in collaborative VR applications.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.13343702

Authors: Moharana, Bhagyabati, Keighrey, Conor, Murray, Niall

Institution: Technological University of the Shannon: Midlands Midwest

Language: English

Topic: Virtual Reality Applications and Impacts

Subfield: Human-Computer Interaction

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: European Commission, Science Foundation Ireland, HORIZON EUROPE Framework Programme

Awards: Ignite the Immersive Media Sector by Enabling New Narrative Visions, G2793989030, Confirm Centre for Smart Manufacturing