Automatic analysis of children's engagement using interactional network features

We explored the automatic analysis of vocal non-verbal cues of a group of children in the context of engagement and collaborative play. For the current study, we defined two types of engagement on groups of children: harmonised and unharmonised. A spontaneous audiovisual corpus with groups of children who collaboratively build a 3D puzzle was collected. With this corpus, we modelled the interactions among children using network-based features representing the centrality and similarity of interactions. The centrality measures how interactions among group members are concentrated on a specific speaker while the similarity measures how similar the interactions are. We examined their discriminative characteristics in harmonised and unharmonised engagement situations. High centrality and low similarity values were found in unharmonised engagement situations. In harmonised engagement situations, we found low centrality and high similarity values. These results suggest that interactional network features are promising for the development of automatic detection of engagement at the group level.