Automatic detection of interaction groups

This paper addresses the problem of detecting interaction groups in an intelligent environment. To understand human activity, we need to identify human actors and their interpersonal links. An interaction group can be seen as basic entity, within which individuals collaborate in order to achieve a common goal. In this regard, the dynamic change of interaction group configuration, i.e. the split and merge of interaction groups, can be seen as indicator of new activities. Our approach takes speech activity detection of individuals forming interaction groups as input. A classical HMM-based approach learning different HMM for the different group configurations did not produce promising results. We propose an approach for detecting interaction group configurations based on the assumption that conversational turn taking is synchronized inside groups. The proposed detector is based on one HMM constructed upon conversational hypotheses. The approach shows good results and thus confirms our co...

• Type: Conference
• Year: 2005
• Where: ICMI
• Authors: Oliver Brdiczka, Jérôme Maisonnasse, Patrick Reignier
• Keywords: Conversational Hypotheses, ICMI 2005, Interaction Group Configurations, Interaction Groups