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Toward an Automatic Prediction of the Sense of Presence in Virtual Reality Environment

Abstract : In human-agent interaction, one key challenge is the evaluation of the user's experience. In the virtual reality domain, the sense of presence and co-presence, reflecting the psychological immersion of the user, is generally assessed through well-grounded subjective post-experience questionnaires. In this article, we aim at presenting a new way to automatically predict the sense of presence and co-presence of a user at the end of an interaction based on specific verbal and non-verbal behavioral cues automatically computed. A random forest algorithm has been applied on a human-agent interaction corpus collected in the specific context of a virtual environment developed to train doctors to break bad news to a virtual patient. The performance of the models demonstrate the capacity to automatically and accurately predict the level of presence and co-presence, but also show the relevancy of the verbal and non-verbal behavioral cues as objective measures of presence.
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Submitted on : Friday, November 8, 2019 - 11:25:35 AM
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Magalie Ochs, Jain Sameer, Jean-Marie Pergandi, Blache Philippe. Toward an Automatic Prediction of the Sense of Presence in Virtual Reality Environment. International Conference on Human-Agent Interaction (HAI), Dec 2018, Southampton, United Kingdom. pp.161-166, ⟨10.1145/3284432.3284452⟩. ⟨hal-01960814⟩



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