%Aigaion2 BibTeX export from Idiap Publications
%Friday 10 May 2024 04:44:53 AM

@INPROCEEDINGS{Favre_ACMMULTIMEDIA_2008,
         author = {Favre, Sarah and Salamin, Hugues and Vinciarelli, Alessandro and Hakkani T{\"{u}}r, Dilek and Garg, N. P.},
       projects = {Idiap, IM2},
          month = {10},
          title = {Role Recognition for Meeting Participants: an Approach Based on Lexical Information and Social Network Analysis},
      booktitle = {ACM International Conference on Multimedia},
           year = {2008},
       location = {Vancouver, Canada},
       crossref = {salamin:rr08-57},
       abstract = {This paper presents experiments on the automatic recognition
of roles in meetings. The proposed approach combines two sources
of information: the lexical choices made by people playing
different roles on one hand, and the Social Networks describing
the interactions between the meeting participants on the other
hand. Both sources lead to role recognition results significantly
higher than chance when used separately, but the best results are
obtained with their combination. Preliminary experiments obtained
over a corpus of 138 meeting recordings (over 45 hours of material)
show that around 70\% of the time is labeled correctly in terms of
role.},
            pdf = {https://publications.idiap.ch/attachments/papers/2008/Favre_ACMMULTIMEDIA_2008.pdf}
}



crossreferenced publications: 
@TECHREPORT{salamin:rr08-57,
         author = {Garg, N. P. and Favre, Sarah and Salamin, Hugues and T{\"{u}}r, D. Hakkani and Vinciarelli, Alessandro},
       projects = {Idiap},
          title = {Role Recognition for Meeting Participants: an Approach Based on Lexical Information and Social Network Analysis},
           type = {Idiap-RR},
         number = {Idiap-RR-57-2008},
           year = {2008},
    institution = {IDIAP},
           note = {To appear in Proceedings of ACM International Conference on Multimedia (2008)},
       abstract = {This paper presents experiments on the automatic recognition of roles in meetings. The proposed approach combines two sources of information: the lexical choices made by people playing different roles on one hand, and the Social Networks describing the interactions between the meeting participants on the other hand. Both sources lead to role recognition results significantly higher than chance when used separately, but the best results are obtained with their combination. Preliminary experiments obtained over a corpus of 138 meeting recordings (over 45 hours of material) show that around 70 percents of the time is labeled correctly in terms of role.},
            pdf = {https://publications.idiap.ch/attachments/reports/2008/salamin-idiap-rr-08-57.pdf},
ipdmembership={multimodal}
}