Speakers role recognition in multiparty audio recordings using social network analysis and duration distribution modeling

Vinciarelli, A. (2007) Speakers role recognition in multiparty audio recordings using social network analysis and duration distribution modeling. IEEE Transactions on Multimedia, 9(6), pp. 1215-1226. (doi:10.1109/TMM.2007.902882)

Full text not currently available from Enlighten.

Publisher's URL: http://dx.doi.org/10.1109/TMM.2007.902882

Abstract

This paper presents two approaches for speaker role recognition in multiparty audio recordings. The experiments are performed over a corpus of 96 radio bulletins corresponding to roughly 19 h of material. Each recording involves, on average, 11 speakers playing one among six roles belonging to a predefined set. Both proposed approaches start by segmenting automatically the recordings into single speaker segments, but perform role recognition using different techniques. The first approach is based on Social Network Analysis, the second relies on the intervention duration distribution across different speakers. The two approaches are used separately and combined and the results show that around 85% of the recording time can be labeled correctly in terms of role.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Vinciarelli, Professor Alessandro
Authors: Vinciarelli, A.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:IEEE Transactions on Multimedia
ISSN:1520-9210

University Staff: Request a correction | Enlighten Editors: Update this record