Automatic Recognition of Emergent Social Roles in Small Group Interactions

This paper investigates the automatic recognition of social roles that emerge naturally in small groups. These roles represent a flexible classification scheme that can generalize across different scenarios of small group interaction. We systematically investigate various verbal and non-verbal cues extracted from turn-taking patterns, vocal expression, and linguistic style to model speakers behavior. The influence of social roles on the behavior cues exhibited by a speaker is modeled using a discriminative approach based on conditional random fields. Experiments performed on several hours of meeting data reveal that social role recognition using conditional random fields achieves an accuracy of 74% in classifying four social roles and outperforms the baseline method on all social role categories . Furthermore , we also demonstrate the effectiveness of our approach by evaluating it on previously unseen scenarios of small group interactions.