Decoding emotions in expressive music performances: A multi-lab replication and extension study

Authors

Jessica Akkermans, Department of Psychology , Goldsmiths, University of London , London , UK.
Renee Schapiro, Department of Psychology , Goldsmiths, University of London , London , UK.
Daniel Müllensiefen, Department of Psychology , Goldsmiths, University of London , London , UK.
Kelly Jakubowski, Department of Music , Durham University , Durham , UK.
Daniel Shanahan, College of Humanities and Social Sciences , Louisiana State University , Baton Rouge , LA , USA.
David Baker, College of Humanities and Social Sciences , Louisiana State University , Baton Rouge , LA , USA.
Veronika Busch, Department of Musicology and Music Education , University of Bremen , Bremen , Germany.
Kai Lothwesen, Department of Musicology and Music Education , University of Bremen , Bremen , Germany.
Paul Elvers, Music Department , Max Planck Institute for Empirical Aesthetics , Frankfurt am Main , Germany.
Timo Fischinger, Music Department , Max Planck Institute for Empirical Aesthetics , Frankfurt am Main , Germany.
Kathrin Schlemmer, Music Department , Catholic University of Eichstätt-Ingolstadt , Eichstaett , Germany.
Klaus Frieler, Institute for Musicology , University of Music "Franz Liszt" Weimar , Hamburg , Germany.

Document Type

Article

Publication Date

9-1-2019

Abstract

With over 560 citations reported on Google Scholar by April 2018, a publication by Juslin and Gabrielsson (1996) presented evidence supporting performers' abilities to communicate, with high accuracy, their intended emotional expressions in music to listeners. Though there have been related studies published on this topic, there has yet to be a direct replication of this paper. A replication is warranted given the paper's influence in the field and the implications of its results. The present experiment joins the recent replication effort by producing a five-lab replication using the original methodology. Expressive performances of seven emotions (e.g. happy, sad, angry, etc.) by professional musicians were recorded using the same three melodies from the original study. Participants ( = 319) were presented with recordings and rated how well each emotion matched the emotional quality using a 0-10 scale. The same instruments from the original study (i.e. violin, voice, and flute) were used, with the addition of piano. In an effort to increase the accessibility of the experiment and allow for a more ecologically-valid environment, the recordings were presented using an internet-based survey platform. As an extension to the original study, this experiment investigated how musicality, emotional intelligence, and emotional contagion might explain individual differences in the decoding process. Results found overall high decoding accuracy (57%) when using emotion ratings aggregated for the sample of participants, similar to the method of analysis from the original study. However, when decoding accuracy was scored for each participant individually the average accuracy was much lower (31%). Unlike in the original study, the voice was found to be the most expressive instrument. Generalised Linear Mixed Effects Regression modelling revealed that musical training and emotional engagement with music positively influences emotion decoding accuracy.

Publication Source (Journal or Book title)

Cognition & emotion

First Page

1099

Last Page

1118

Recommended Citation

Akkermans, J., Schapiro, R., Müllensiefen, D., Jakubowski, K., Shanahan, D., Baker, D., Busch, V., Lothwesen, K., Elvers, P., Fischinger, T., Schlemmer, K., & Frieler, K. (2019). Decoding emotions in expressive music performances: A multi-lab replication and extension study. Cognition & emotion, 33 (6), 1099-1118. https://doi.org/10.1080/02699931.2018.1541312