Multimodal Analysis of Cohesion in Multi-party Interactions

Reshmashree B Kantharaju (1) , Caroline Langlet , Mukesh Barange , Chloé Clavel (2, 3, 4) , Catherine I Pelachaud

1 ISIR - Institut des Systèmes Intelligents et de Robotique
2 S2A - Signal, Statistique et Apprentissage
3 LTCI - Laboratoire Traitement et Communication de l'Information
4 Télécom Paris

Group cohesion is an emergent phenomenon that describes the tendency of the group members' shared commitment to group tasks and the interpersonal attraction among them. This paper presents a multimodal analysis of group cohesion using a corpus of multi-party interactions. 16 two-minute segments annotated with cohesion data is used. We define three layers of modalities: non-verbal social cues, dialogue acts and interruptions. The initial analysis is performed at the individual level and later, we combine the different modalities to observe their impact on perceived level of cohesion. Results indicate that occurrence of laughter and interruption are higher in high cohesive segments. We also observed that, dialogue acts and head nods did not have an impact on the level of cohesion by itself. However, when combined there was an impact on the perceived level of cohesion. Overall, the analysis shows that multimodal cues are crucial for accurate analysis of group cohesion.

Mots clés: Cohesion; Dialogue acts; Non-verbal behaviours; Interruptions

Domaines: Informatique [cs]; Interface homme-machine [cs.HC]

Reshmashree B Kantharaju, Caroline Langlet, Mukesh Barange, Chloé Clavel, Catherine I Pelachaud. Multimodal Analysis of Cohesion in Multi-party Interactions. LREC, 2020, Marseille, France. ⟨hal-02953469⟩