Speaker diarization of multi-party conversations using participants role information: political debates and professional meetings

Valente, F. and Vinciarelli, A. (2014) Speaker diarization of multi-party conversations using participants role information: political debates and professional meetings. In: Murray-Smith, R. (ed.) Mobile Social Signal Processing. Series: Lecture notes in computer science (8045). Springer: Heidelberg, pp. 22-33. ISBN 9783642543241 (doi: 10.1007/978-3-642-54325-8_3)

Abstract

Speaker Diarization aims at inferring who spoke when in an audio stream and involves two simultaneous unsupervised tasks: (1) the estimation of the number of speakers, and (2) the association of speech segments to each speaker. Most of the recent efforts in the domain have addressed the problem using machine learning techniques or statistical methods (for a review see [11]) ignoring the fact that the data consists of instances of human conversations.

• Item Type: Book Sections
• Status: Published
• Glasgow Author(s) Enlighten ID: Vinciarelli, Professor Alessandro
• Authors: Valente, F., and Vinciarelli, A.
• College/School: College of Science and Engineering > School of Computing Science
• Publisher: Springer
• ISBN: 9783642543241
• Copyright Holders: Copyright © 2014 The Authors