Decision-Level Fusion for Audio-Visual Laughter Detection

B. Reuderink, Mannes Poel, Khiet Phuong Truong, Ronald Walter Poppe, Maja Pantic

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

    22 Citations (Scopus)
    3 Downloads (Pure)


    Laughter is a highly variable signal, which can be caused by a spectrum of emotions. This makes the automatic detection of laugh- ter a challenging, but interesting task. We perform automatic laughter detection using audio-visual data from the AMI Meeting Corpus. Audio- visual laughter detection is performed by fusing the results of separate audio and video classifiers on the decision level. This results in laughter detection with a significantly higher AUC-ROC than single-modality classification.
    Original languageUndefined
    Title of host publication5th International Workshop, MLMI 2008
    EditorsAndrei Popescu-Belis, Rainer Stiefelhagen
    Place of PublicationBerlin
    Number of pages12
    ISBN (Print)978-3-540-85852-2
    Publication statusPublished - Sept 2008
    Event5th International Workshop on Machine Learning and Multimodal Interaction, MLMI 2008: 5th Joint Workshop on Machine Learning and Multimodal Interaction - Utrecht, the Netherlands, Berlin
    Duration: 8 Sept 200810 Sept 2008

    Publication series

    NameLecture Notes on Computer Science
    PublisherSpringer Verlag
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    Conference5th International Workshop on Machine Learning and Multimodal Interaction, MLMI 2008
    Other8-10 September 2008


    • EWI-13404
    • IR-62452
    • METIS-256121
    • HMI-CI: Computational Intelligence

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