Semantic Contours in Tracks Based on Emotional Tags

  • Michael Kai Petersen
  • Lars Kai Hansen
  • Andrius Butkus
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5493)

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.

Keywords

Pattern recognition emotions text processing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Michael Kai Petersen
    • 1
  • Lars Kai Hansen
    • 1
  • Andrius Butkus
    • 1
  1. 1.DTU InformaticsTechnical University of DenmarkKgs.LyngbyDenmark

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