Detrended Fluctuation Analysis of Music Signals: Danceability Estimation and further Semantic Characterization
نویسندگان
چکیده
Detrended fluctuation analysis (DFA) has been proposed by Peng et al. [1] to be used on biomedical data. It originates from fractal analysis and reveals correlations within data series across different time scales. Jennings et al. [2] used a DFA-derived feature, the detrended variance fluctuation exponent, for musical genre classification introducing the method to the music analysis field. In this paper we further exploit the relation of this low-level feature to semantic music descriptions. It was computed on 7750 tracks with manually annotated semantic labels like “Energetic” or “Melancholic”. We found statistically strong associations between some of these labels and this feature supporting the hypothesis that it can be linked to a musical attribute which might be described as “danceability”.
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