Role recognition in multiparty recordings using social affiliation networks and discrete distributions

Favre, S., Salamin, H., Dines, J. and Vinciarelli, A. (2008) Role recognition in multiparty recordings using social affiliation networks and discrete distributions. In: ICMI '08 Proceedings of the 10th International Conference on Multimodal Interfaces, Chania, Greece, October 20-22, 2008, pp. 29-36. (doi:10.1145/1452392.1452401)

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Publisher's URL: http://dx.doi.org/10.1145/1452392.1452401

Abstract

This paper presents an approach for the recognition of roles in multiparty recordings. The approach includes two major stages: extraction of Social Affiliation Networks (speaker diarization and representation of people in terms of their social interactions), and role recognition (application of discrete probability distributions to map people into roles). The experiments are performed over several corpora, including broadcast data and meeting recordings, for a total of roughly 90 hours of material. The results are satisfactory for the broadcast data (around 80 percent of the data time correctly labeled in terms of role), while they still must be improved in the case of the meeting recordings (around 45 percent of the data time correctly labeled). In both cases, the approach outperforms significantly chance.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Salamin, Mr Hugues and Vinciarelli, Professor Alessandro
Authors: Favre, S., Salamin, H., Dines, J., and Vinciarelli, A.
College/School:College of Science and Engineering > School of Computing Science

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