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"Hardness" as a semantic audio descriptor for music using automatic feature extraction

dc.contributor.authorCzedik-Eysenberg, Isabella
dc.contributor.authorKnauf, Denis
dc.contributor.authorReuter, Christoph
dc.contributor.editorEibl, Maximilian
dc.contributor.editorGaedke, Martin
dc.date.accessioned2017-08-28T23:48:51Z
dc.date.available2017-08-28T23:48:51Z
dc.date.issued2017
dc.description.abstractThe quality of "hardness" in music is an attribute that is most commonly associated with genres like metal or hard rock. However, other examples of music raise the question of whether there is a genre-independent general dimension of "hardness" that can be obtained from the signal automatically based on psychoacoustical features. In listening experiments 40 subjects were asked to rate 62 music excerpts according to their hardness. Using MATLAB toolboxes, a set of features covering spectral and temporal sound properties was obtained from the stimuli and investigated in terms of their correlation with the subjective ratings. By means of multiple linear regression analysis a model for musical hardness was constructed which shows a correlation of r = 0.86 with the experimental results. This proposes musical hardness as a useful high level descriptor for analysing collections of music. In ongoing experiments the fitness of this model is being further evaluated.en
dc.identifier.doi10.18420/in2017_06
dc.identifier.isbn978-3-88579-669-5
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik, Bonn
dc.relation.ispartofINFORMATIK 2017
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-275
dc.subjectMusic
dc.subjectSemantic Audio Feature Extraction
dc.subjectHardness
dc.subjectHeaviness
dc.subjectMetal
dc.subjectHigh Level Descriptor
dc.title"Hardness" as a semantic audio descriptor for music using automatic feature extractionen
gi.citation.endPage110
gi.citation.startPage101
gi.conference.date25.-29. September 2017
gi.conference.locationChemnitz
gi.conference.sessiontitleMusik trifft Informatik

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