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

Magalie Ochs (1, 2, 3) , Jain Sameer (4) , Jean-Marie Pergandi (5) , Blache Philippe (4)

1 DIMAG - Data, Information & content MAnagement Group
2 LIS - Laboratoire d'Informatique et des Systèmes (LIS) (Marseille, Toulon)
3 AMU - Aix Marseille Université
4 LPL - Laboratoire Parole et Langage
5 CRVM - Centre de Réalité Virtuelle de la Méditerranée

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.

Domaines: Modélisation et simulation; Interface homme-machine [cs.HC]; Intelligence artificielle [cs.AI]

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⟩