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

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.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-08-19
DOI
https://doi.org/10.5281/zenodo.13343703
Primary Topic
Virtual Reality Applications and Impacts
Type
article
Field-Weighted Citation Impact
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article

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

Zenodo (CERN European Organization for Nuclear Research)
Virtual Reality Applications and Impacts
article

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

article en

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.

Zenodo (CERN European Organization for Nuclear Research)
Shannon Applied Biotechnology Centre (IE), Technological University of the Shannon: Midlands Midwest
Openalex Percentile: Top 58%
Virtual Reality Applications and Impacts
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