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Audience Facial Expressions Detected by Automated Face Analysis Software Reflect Emotions in Music by Diana Kayser; Hauke Egermann; Nick E. Barraclough is a Psychology article available to read on EtoBox.

What is Audience Facial Expressions Detected by Automated Face Analysis Software Reflect Emotions in Music about?

An abundance of studies on emotional experiences in response to music have been published over the past decades, however, most have been carried out in controlled laboratory settings and rely on subjective reports. Facial expressions have been occasionally assessed but measured using intrusive methods such as facial electromyography (fEMG). The present study investigated emotional experiences of fifty participants in a live concert. Our aims were to explore whether automated face analysis could detect facial expressions of emotion in a group of people in an ecologically valid listening context, to determine whether emotions expressed by the music predicted specific facial expressions and examine whether facial expressions of emotion could be used to predict subjective ratings of pleasantness and activation. During the concert, participants were filmed and facial expressions were subsequently analyzed with automated face analysis software. Self-report on participants’ subjective experience of pleasantness and activation were collected after the concert for all pieces (two happy, two sad). Our results show that the pieces that expressed sadness resulted in more facial expressions of

Who reads Audience Facial Expressions Detected by Automated Face Analysis Software Reflect Emotions in Music?

Author

Diana Kayser; Hauke Egermann; Nick E. Barraclough

Publisher

Springer Science and Business Media LLC

Published

2021

Language

EN

Field

Psychology (Social Sciences)