Speaker change detection and tracking in real-time news broadcasting analysis

  • Authors:
  • Lie Lu;Hong-Jiang Zhang

  • Affiliations:
  • Microsoft Research, Asia Beijing, China;Microsoft Research, Asia Beijing, China

  • Venue:
  • Proceedings of the tenth ACM international conference on Multimedia
  • Year:
  • 2002

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Abstract

This paper addresses the problem of real time speaker change detection and speaker tracking in broadcasted news video analysis. In such a case, both speaker identities and number of speakers are assumed unknown. A two-step speaker change detection algorithm, including potential change detection and refinement, is proposed. Speaker tracking is performed based on the results of speaker change detection. A Bayesian Fusion method is used to fuse multiple audio features to get a more reliable result. The algorithm has low complexity and runs in real-time with a very limited delay in analysis. Our experiments show that the algorithms produce very satisfactory results.