Music Emotion Maps in Arousal-Valence Space - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2016

Music Emotion Maps in Arousal-Valence Space

Jacek Grekow
  • Function : Author
  • PersonId : 999213

Abstract

In this article we present the approach in which the detection of emotion is modeled by the pertinent regression problem. Conducting experiments required building a database, annotation of samples by music experts, construction of regressors, attribute selection, and analysis of selected musical compositions. We obtained a satisfactory correlation coefficient value for SVM for regression algorithm at 0.88 for arousal and 0.74 for valence. The result applying regressors are emotion maps of the musical compositions. They provide new knowledge about the distribution of emotions in musical compositions. They reveal new knowledge that had only been available to music experts until this point.
Fichier principal
Vignette du fichier
419526_1_En_60_Chapter.pdf (258.65 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01637515 , version 1 (17-11-2017)

Licence

Attribution - CC BY 4.0

Identifiers

Cite

Jacek Grekow. Music Emotion Maps in Arousal-Valence Space. 15th IFIP International Conference on Computer Information Systems and Industrial Management (CISIM), Sep 2016, Vilnius, Lithuania. pp.697-706, ⟨10.1007/978-3-319-45378-1_60⟩. ⟨hal-01637515⟩
120 View
813 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More