Work

Evaluating Multimodal Behavioral Features for Public Speaking Assessment in Virtual Reality

Year: 2025

Type: conference-paper

Abstract: Public speaking (PS) self-assessment remains challenging due to multiple behavioral dimensions and a lack of objective evaluation methods.Virtual reality (VR) offers immersive training environments with automatic performance analysis capabilities.However, current evaluation systems use ad hoc metrics lacking transparency and reproducibility.No comprehensive set of multimodal, contextindependent behavioral cues exists for interpretable user feedback.We propose verbal and nonverbal features meeting three criteria: automatic measurement capability, context independence, and user interpretability.Using a multimodal corpus of VR presentations by 60 participants, we extracted 47 behavioral features via the Meta Quest Pro headset.Expert assessment used 7-point Likert scales.Correlation analysis and machine learning models demonstrate this feature set provides a relevant basis for automated PS assessment in VR.

Source: ACM International Conference on Intelligent Virtual Agents (IVA)

DOI: 10.1145/3717511.3749301

Authors: Marion Ristorcelli, Elodie Etienne, Michaël Schyns, Rémy Casanova, Magalie Ochs

Institutions: Aix-Marseille Université, Laboratoire d’Informatique et Systèmes, University of Liège, Institut des Sciences du Mouvement Etienne-Jules Marey

Language: English

Topic: Virtual Reality Applications and Impacts

Subfield: Human-Computer Interaction

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: Agence Nationale de la Recherche

Award: viRtual bEhaVioral skIlls TrAining for pubLIc SpEaking