Semantic Contours in Tracks Based on Emotional Tags

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    Abstract

    Outlining a high level cognitive approach to how we select media based on affective user preferences, we model the latent semantics of lyrics as patterns of emotional components. Using a selection of affective last.fm tags as top-down emotional buoys, we apply LSA latent semantic analysis to bottom-up represent the correlation of terms and song lyrics in a vector space that reflects the emotional context. Analyzing the resulting patterns of affective components, by comparing them against last.fm tag clouds describing the corresponding songs, we propose that it might be feasible to automatically generate affective user preferences based on song lyrics.
    Original languageEnglish
    Title of host publicationComputer Music Modeling and Retrieval. : Genesis of Meaning in Sound and Music
    Number of pages285
    VolumeVolume 5493/2010
    PublisherSpringer
    Publication date2009
    Edition1st
    Pages45-66
    ISBN (Print)978-3-642-02517-4
    DOIs
    Publication statusPublished - 2009
    EventComputer Music Modeling and Retrieval. Genesis of Meaning in Sound and Music - Copenhagen, Denmark,
    Duration: 1 Jan 2008 → …
    Conference number: 5th

    Conference

    ConferenceComputer Music Modeling and Retrieval. Genesis of Meaning in Sound and Music
    Number5th
    CityCopenhagen, Denmark,
    Period01/01/2008 → …
    SeriesLecture Notes in Computer Science
    Volume5493
    ISSN0302-9743

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