Music playlist generation by assimilating GMMs into SOMs

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    11 Citations (Scopus)

    Abstract

    A method for music playlist generation, using assimilated Gaussian mixture models (GMMs) in self organizing maps (SOMs) is presented. Traditionally, the neurons in a SOM are represented by vectors, but in this paper we propose to use GMMs instead. To this end, we introduce a method to adapt a GMM such that its distance to a second GMM decreases at a controllable rate. Self organization is demonstrated using a small music database and a music classification task.
    Original languageUndefined
    Pages (from-to)1396-1402
    Number of pages7
    JournalPattern recognition letters
    Volume31
    Issue number11
    DOIs
    Publication statusPublished - Aug 2010

    Keywords

    • EWI-18345
    • Self organization
    • Earth mover’s distance
    • IR-72797
    • Gaussian mixtures
    • Music playlists
    • METIS-271002
    • Genre classification

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