Influences of rhythm- and timbre-related musical features on characteristics of music-induced movement

Birgitta Burger, Marc R Thompson, Geoff Luck, Suvi Saarikallio, Petri Toiviainen, Birgitta Burger, Marc R Thompson, Geoff Luck, Suvi Saarikallio, Petri Toiviainen

Abstract

Music makes us move. Several factors can affect the characteristics of such movements, including individual factors or musical features. For this study, we investigated the effect of rhythm- and timbre-related musical features as well as tempo on movement characteristics. Sixty participants were presented with 30 musical stimuli representing different styles of popular music, and instructed to move along with the music. Optical motion capture was used to record participants' movements. Subsequently, eight movement features and four rhythm- and timbre-related musical features were computationally extracted from the data, while the tempo was assessed in a perceptual experiment. A subsequent correlational analysis revealed that, for instance, clear pulses seemed to be embodied with the whole body, i.e., by using various movement types of different body parts, whereas spectral flux and percussiveness were found to be more distinctly related to certain body parts, such as head and hand movement. A series of ANOVAs with the stimuli being divided into three groups of five stimuli each based on the tempo revealed no significant differences between the groups, suggesting that the tempo of our stimuli set failed to have an effect on the movement features. In general, the results can be linked to the framework of embodied music cognition, as they show that body movements are used to reflect, imitate, and predict musical characteristics.

Keywords: dance; motion capture; music-induced movement; musical feature extraction; pulse clarity; spectral flux.

Figures

Figure 1
Figure 1
Marker and joint locations. (A) Anterior and posterior view of the marker placement on the participants’ bodies; (B) Anterior view of the marker locations as stick figure illustration; (C) Anterior view of the locations of the secondary markers/joints used in the analysis.
Figure 2
Figure 2
Fluctuation spectra of two stimuli used in the study. (A) Peaks at a regular distance of 0.28 Hz, with the highest peak at 4.56 Hz and other clear peaks at 2.29, 6.85, and 9.13 Hz, suggesting clear pulses and periodicity (stimulus 1, see Appendix). (B) Markedly lower magnitude values, a less periodic pattern of peaks, and more noise, suggesting low pulse clarity (stimulus 21, see Appendix).
Figure 3
Figure 3
Spectrograms (sec. 10–20) of sub-band no. 2 (50–100 Hz) of two stimuli used in the study. (A) High amount of temporal change (red represents high energy at the respective time and frequency, whereas blue represents low energy; see color bar) resulting in high value for Sub-Band Flux (stimulus 26, see Appendix). (B) Low amount of temporal change resulting in low Sub-Band Flux (stimulus 5, see Appendix).

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