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Automatic Detection of Interaction Groups (2005)
| Content Provider | CiteSeerX |
|---|---|
| Author | Brdiczka, Oliver Maisonnasse, Jérôme Reignier, Patrick |
| Description | 2005 International Conference on Multimodal interaction, ICMI '05, Trento It 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 conversational hypotheses. |
| File Format | |
| Language | English |
| Publisher Date | 2005-01-01 |
| Access Restriction | Open |
| Subject Keyword | Interpersonal Link Automatic Detection Human Actor Good Result Intelligent Environment Interaction Group Configuration Classical Hmm-based Approach Common Goal Different Hmm Different Group Configuration Conversational Hypothesis Human Activity Dynamic Change Interaction Group Basic Entity Conversational Turn Taking Speech Activity Detection New Activity |
| Content Type | Text |
| Resource Type | Article |
