A cluster-voting approach for speaker diarization and linking of Australian broadcast news recordings
Ghaemmaghami, Houman, Dean, David, & Sridharan, Sridha (2015) A cluster-voting approach for speaker diarization and linking of Australian broadcast news recordings. In Proceedings of the 40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2015, IEEE, Brisbane, Australia, pp. 4829-4833.
We present a clustering-only approach to the problem of speaker diarization to eliminate the need for the commonly employed and computationally expensive Viterbi segmentation and realignment stage. We use multiple linear segmentations of a recording and carry out complete-linkage clustering within each segmentation scenario to obtain a set of clustering decisions for each case. We then collect all clustering decisions, across all cases, to compute a pairwise vote between the segments and conduct complete-linkage clustering to cluster them at a resolution equal to the minimum segment length used in the linear segmentations. We use our proposed cluster-voting approach to carry out speaker diarization and linking across the SAIVT-BNEWS corpus of Australian broadcast news data. We compare our technique to an equivalent baseline system with Viterbi realignment and show that our approach can outperform the baseline technique with respect to the diarization error rate (DER) and attribution error rate (AER).
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|Item Type:||Conference Paper|
|Keywords:||cluster-voting, complete-linkage clustering, speaker diarization, Viterbi realignment|
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2015 [please consult the authors]|
|Deposited On:||07 Jul 2015 23:25|
|Last Modified:||11 Sep 2015 09:29|
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