%Aigaion2 BibTeX export from Idiap Publications
%Thursday 21 November 2024 01:09:48 PM

@TECHREPORT{vijayasenan:rr07-31,
         author = {Vijayasenan, Deepu and Valente, Fabio and Bourlard, Herv{\'{e}}},
       projects = {Idiap},
          title = {AGGLOMERATIVE INFORMATION BOTTLENECK FOR SPEAKER DIARIZATION OF MEETINGS DATA},
           type = {Idiap-RR},
         number = {Idiap-RR-31-2007},
           year = {2007},
    institution = {IDIAP},
       abstract = {In this paper, we investigate the use of agglomerative Information Bottleneck (aIB) clustering for the speaker diarization task of meetings data. In contrary to the state-of-the-art diarization systems that models individual speakers with Gaussian Mixture Models, the proposed algorithm is completely non parametric . Both clustering and model selection issues of non-parametric models are addressed in this work. The proposed algorithm is evaluated on meeting data on the RT06 evaluation data set. The system is able to achieve Diarization Error Rates comparable to state-of-the-art systems at a much lower computational complexity.},
            pdf = {https://publications.idiap.ch/attachments/reports/2007/vijayasenan-idiap-rr-07-31.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2007/vijayasenan-idiap-rr-07-31.ps.gz},
ipdmembership={speech},
}