Automatic Dominance Detection in Meetings using easily obtainable features

R.J. Rienks, Dirk K.J. Heylen

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    43 Citations (Scopus)
    56 Downloads (Pure)

    Abstract

    We show that, using a Support Vector Machine classifier, it is possible to determine with a 75% success rate who dominated a particular meeting on the basis of a few basic features. We discuss the corpus we have used, the way we had people judge dominance and the features that were used.
    Original languageUndefined
    Title of host publicationRevised Selected Papers of the 2nd Joint Workshop on Multimodal Interaction and Related Machine Learning Algorithms MLMI 2005
    EditorsH. Bourlard, S. Renals
    Place of PublicationBerlin
    PublisherSpringer
    Pages76-86
    Number of pages11
    ISBN (Print)978-3-540-32549-9
    DOIs
    Publication statusPublished - 2006
    Event2nd International Workshop on Machine Learning for Multimodal Interaction, MLMI 2005 - Edinburgh, United Kingdom
    Duration: 11 Jul 200513 Jul 2005
    Conference number: MLMI

    Publication series

    NameLecture Notes in Computer Science
    PublisherSpringer Verlag
    Number10
    Volume3869

    Workshop

    Workshop2nd International Workshop on Machine Learning for Multimodal Interaction, MLMI 2005
    CountryUnited Kingdom
    CityEdinburgh
    Period11/07/0513/07/05

    Keywords

    • HMI-MI: MULTIMODAL INTERACTIONS
    • EC Grant Agreement nr.: FP6/506811
    • IR-66668
    • METIS-237665
    • EWI-8309

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