%Aigaion2 BibTeX export from Idiap Publications
%Thursday 21 November 2024 12:54:12 PM

@INPROCEEDINGS{lathoud04a,
         author = {Lathoud, Guillaume and McCowan, Iain A. and Odobez, Jean-Marc},
       projects = {Idiap},
          month = {5},
          title = {Unsupervised {L}ocation-{B}ased {S}egmentation of {M}ulti-{P}arty {S}peech},
      booktitle = {{P}roceedings of the 2004 {ICASSP-NIST} {M}eeting {R}ecognition {W}orkshop},
           year = {2004},
        address = {Montreal, Canada},
           note = {IDIAP-RR 04-14},
       crossref = {lathoud-rr-04-14},
       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 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/papers/2004/lathoud04a.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/papers/2004/lathoud04a.ps.gz},
ipdinar={2004},
ipdmembership={speech, vision},
}



crossreferenced publications: 
@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},
}