Towards Predicting Expressed Emotion in Music from Pairwise Comparisons

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

AbstractWe introduce five different 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 and shows a difference despite similar classification error. The variation in predictions across subjects and the difference in ranking is investigated visually in the AV space and quantified using Kendall's tau.
Keywordsexpressed emotion, pairwise comparison, Gaussian process, Generalized Linear models
TypeConference paper [With referee]
Conference9th Sound and Music Computing Conference (SMC) Illusions
Year2012    Month July
Electronic version(s)[pdf]
BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing

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