Detrended Fluctuation Analysis of Music Signals: Danceability Estimation and Further Semantic Characterization
The detrended fluctuation analysis (DFA) has been proposed by Peng et al. and was first applied in biomedical analysis. Jennings et al. introduced the method to the field of music analysis by using the DFA exponent for musical genre classification. In this paper we further exploit the relation of this low-level feature to semantic music descriptions. The feature has been computed on a large-scale collection of 7750 tracks for which manually annotated semantic labels like "energetic" or "melancholic" where available. Associations with high statistical significance could be found between some of these labels and the DFA exponent. The findings sustain the hypothesis that this feature can be linked to a musical attribute which might be described as "danceability".
Click to purchase paper or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members, $5 for AES members and is free for E-Library subscribers.