A Robust Speaker Clustering Algorithm

In this paper, we present a novel speaker segmentation and clustering algorithm. The algorithm automatically performs both speaker segmentation and clustering without any prior knowledge of the identities or the number of speakers. Advantages of this algorithm over other approaches are: no need for training/development data, no threshold adjustment requirements, and robustness to different data conditions. This paper also reports the performance of the algorithm on different datasets released by NIST with different initial conditions and parameter settings. The consistently low speaker diarization error rate clearly indicates the robustness of the algorithm.


Published in:
IEEE Automatic Speech Recognition Understanding Workshop
Presented at:
IEEE Automatic Speech Recognition Understanding Workshop
Year:
2003
Keywords:
Note:
IDIAP-RR 03-38
Laboratories:




 Record created 2006-03-10, last modified 2018-03-17

n/a:
Download fulltextPDF
External links:
Download fulltextURL
Download fulltextRelated documents
Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)