Data-Driven Generation of Eyes and Head Movements of a Social Robot in Multiparty Conversation - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

Data-Driven Generation of Eyes and Head Movements of a Social Robot in Multiparty Conversation

Résumé

Given the importance of gaze in Human-Robot Interactions (HRI), many gaze control models have been developed. However, these models are mostly built for dyadic face-to-face interaction. Gaze control models for multiparty interaction are more scarce. We here propose and evaluate data-driven gaze control models for a robot game animator in a three-party interaction. More precisely, we used Long Short-Term Memory networks to predict gaze target and context-aware head movements given robot’s communication intents and observed activities of its human partners. After comparing objective performance of our data-driven model with a baseline and ground truth data, an online audiovisual perception study was conducted to compare the acceptability of these control models in comparison with low-anchor incongruent speech and gaze sequences driving the Furhat robot. The results show that our data-driven prediction of gaze targets is viable, but that third-party raters are not so sensitive to controls with congruent head movements.
Fichier principal
Vignette du fichier
lh_ICSR2023.pdf (1.23 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04335472 , version 1 (11-12-2023)

Identifiants

Citer

Léa Haefflinger, Frédéric Elisei, Béatrice Bouchot, Brice Varini, Gérard Bailly. Data-Driven Generation of Eyes and Head Movements of a Social Robot in Multiparty Conversation. ICSR 2023 - 15th International Conference on Social Robotics (ICSR 2023), Dec 2023, Doha, Qatar. pp.191-203, ⟨10.1007/978-981-99-8715-3_17⟩. ⟨hal-04335472⟩
48 Consultations
33 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More