Role recognition for meeting participants: an approach based on lexical information and social network analysis

Authors:
Neha P. Garg;Sarah Favre;Hugues Salamin;Dilek Hakkani Tür;Alessandro Vinciarelli
Affiliations:
Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland and International Computer Science Institute, Berkeley, CA, USA;Idiap Research Institute, Martigny, and Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland;Idiap Research Institute, Martigny, and Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland;International Computer Science Institute, Berkeley, CA, USA;Idiap Research Institute, Martigny, and Ecole Polytechnique Federale de Lausanne, Lausanne, Switzerland
Venue:
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Year:
2008

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Abstract

This paper presents experiments on the automatic recognition of roles in meetings. The proposed approach combines two sources of information: the lexical choices made by people playing different roles on one hand, and the Social Networks describing the interactions between the meeting participants on the other hand. Both sources lead to role recognition results significantly higher than chance when used separately, but the best results are obtained with their combination. Preliminary experiments obtained over a corpus of 138 meeting recordings (over 45 hours of material) show that around 70% of the time is labeled correctly in terms of role.