CONF ajmera-rr-03-38b/IDIAP A Robust Speaker Clustering Algorithm Ajmera, Jitendra Wooters, Charles EXTERNAL https://publications.idiap.ch/attachments/reports/2003/ajmera2003asru.pdf PUBLIC https://publications.idiap.ch/index.php/publications/showcite/ajmera-rr-03-38 Related documents IEEE Automatic Speech Recognition Understanding Workshop 2003 IDIAP-RR 03-38 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. REPORT ajmera-rr-03-38/IDIAP A Robust Speaker Clustering Algorithm Ajmera, Jitendra Wooters, Charles EXTERNAL https://publications.idiap.ch/attachments/reports/2003/rr03-38.pdf PUBLIC Idiap-RR-38-2003 2003 IDIAP To appear in IEEE ASRU 2003 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.