Towards Predicting Expressed Emotion in Music from Pairwise Comparisons

Jens Madsen, Bjørn Sand Jensen, Jan Larsen, Jens Brehm Nielsen

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    We introduce five regression models for the modeling of expressed emotion in music using data obtained in a two alternative forced choice listening experiment. The predictive performance of the proposed models is compared using learning curves, showing that all models converge to produce a similar classification error. The predictive ranking of the models is compared using Kendall's tau rank correlation coefficient which shows a difference despite similar classification error. The variation in predictions across subjects and the difference in ranking is investigated visually in the arousal-valence space and quantified using Kendall's tau.
    Original languageEnglish
    Title of host publicationProceedings of the 9th Sound and Music Computing Conference
    Publication date2012
    Publication statusPublished - 2012
    Event9th Sound and Music Computing Conference (SMC 2012) - Aalborg University Copenhagen, Copenhagen, Denmark
    Duration: 11 Jul 201214 Jul 2012


    Conference9th Sound and Music Computing Conference (SMC 2012)
    LocationAalborg University Copenhagen
    Internet address

    Bibliographical note

    This is an open-access article distributed under the terms of the Creative Commons Attribution 3.0 Unported License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


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