@inproceedings{44323d973cdb43f4aa67f5b725b08b2e,
title = "Computational Multimodal Models of Users{\textquoteright} Interactional Trust in Multiparty Human-Robot Interaction",
abstract = "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.",
keywords = "HRI, affective computing, trust",
author = "Marc Hulcelle and Giovanna Varni and Nicolas Rollet and Chlo{\'e} Clavel",
note = "Publisher Copyright: {\textcopyright} 2023, Springer Nature Switzerland AG.; 26th International Conference on Pattern Recognition, ICPR 2022 Workshops ; Conference date: 21-08-2022 Through 25-08-2022",
year = "2023",
month = jan,
day = "1",
doi = "10.1007/978-3-031-37660-3\_16",
language = "English",
isbn = "9783031376597",
series = "Lecture Notes in Computer Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "225--239",
editor = "Jean-Jacques Rousseau and Bill Kapralos",
booktitle = "Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges - Proceedings",
}