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Communication Dans Un Congrès Année : 2023

Computational Multimodal Models of Users’ Interactional Trust in Multiparty Human-Robot Interaction

Résumé

In this paper, we present multimodal computational models of interactional trust in a humans-robot interaction scenario. We address trust modeling as a binary as well as a multi-class classification problem. We also investigate how early- and late-fusion of modalities impact trust modeling. Our results indicate that early-fusion performs better in both the binary and multi-class formulations, meaning that modalities have co-dependencies when studying trust. We also run a SHapley Additive exPlanation (SHAP) values analysis for a Random Forest in the binary classification problem, as it is the model with the best results, to explore which multimodal features are the most relevant to detect trust or mistrust

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Dates et versions

hal-04276738 , version 1 (09-11-2023)

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Marc Hulcelle, Giovanna Varni, Nicolas Rollet, Chloé Clavel. Computational Multimodal Models of Users’ Interactional Trust in Multiparty Human-Robot Interaction. ICPR 2022: Pattern Recognition, Computer Vision, and Image Processing, Aug 2022, Montréal, Canada. pp.225-239, ⟨10.1007/978-3-031-37660-3_16⟩. ⟨hal-04276738⟩
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