11th Annual Conference of the International Speech Communication Association

Makuhari, Chiba, Japan
September 26-30. 2010

Bayes Factor Based Speaker Segmentation for Speaker Diarization

D. Wang, Robert Vogt, Sridha Sridharan

Queensland University of Technology, Australia

This paper proposes the use of the Bayes Factor as a distance metric for speaker segmentation within a speaker diarization system. The proposed approach uses a pair of constant sized, sliding windows to compute the value of the Bayes Factor between the adjacent windows over the entire audio. Results obtained on the 2002 Rich Transcription Evaluation dataset show an improved segmentation performance compared to previous approaches reported in literature using the Generalized Likelihood Ratio. When applied in a speaker diarization system, this approach results in a 5.1% relative improvement in the overall Diarization Error Rate compared to the baseline.

Full Paper

Bibliographic reference.  Wang, D. / Vogt, Robert / Sridharan, Sridha (2010): "Bayes factor based speaker segmentation for speaker diarization", In INTERSPEECH-2010, 1405-1408.