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@TECHREPORT{lathoud-rr-04-14,
         author = {Lathoud, Guillaume and McCowan, Iain A. and Odobez, Jean-Marc},
       projects = {Idiap},
          title = {{S}hort-{T}erm {S}patio-{T}emporal {C}lustering of {S}poradic and {C}oncurrent Events},
           type = {Idiap-RR},
         number = {Idiap-RR-14-2004},
           year = {2004},
    institution = {IDIAP},
        address = {Martigny, Switzerland},
           note = {Published in ``Proceedings of the 2004 ICASSP-NIST Meeting Recognition Workshop''},
       abstract = {Accurate detection and segmentation of spontaneous multi-party speech is crucial for a variety of applications, including speech acquisition and recognition, as well as higher-level event recognition. However, the highly sporadic nature of spontaneous speech makes this task difficult. Moreover, multi-party speech contains many overlaps. We propose to attack this problem as a multitarget tracking task, using location cues only. In order to best deal with high sporadicity, we propose a novel, generic, short-term clustering algorithm that can track multiple objects for a low computational cost. The proposed approach is online, fully deterministic and can run in real-time. In an application to real meeting data, the algorithm produces high precision speech segmentation.},
            pdf = {https://publications.idiap.ch/attachments/reports/2004/rr-04-14.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2004/rr-04-14.ps.gz},
ipdinar={2004},
ipdmembership={speech, vision},
language={English},
}