Examining Emotion Perception Agreement in Live Music Performance
Author(s) -
Simin Yang,
Courtney N. Reed,
Elaine Chew,
Mathieu Barthet
Publication year - 2021
Publication title -
ieee transactions on affective computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.309
H-Index - 67
ISSN - 1949-3045
DOI - 10.1109/taffc.2021.3093787
Subject(s) - computing and processing , robotics and control systems , signal processing and analysis
Current music emotion recognition (MER) systems rely on emotion data averaged across listeners and over time to infer the emotion expressed by a musical piece, often neglecting time- and listener-dependent factors. These limitations can restrict the efficacy of MER systems and cause misjudgements. We present two exploratory studies on music emotion perception. First, in a live music concert setting, fifteen audience members annotated perceived emotion in the valence-arousal space over time using a mobile application. Analyses of inter-rater reliability yielded widely varying levels of agreement in the perceived emotions. A follow-up lab-based study to uncover the reasons for such variability was conducted, where twenty-one participants annotated their perceived emotions whilst viewing and listening to a video recording of the original performance and offered open-ended explanations. Thematic analysis revealed salient features and interpretations that help describe the cognitive processes underlying music emotion perception. Some of the results confirm known findings of music perception and MER studies. Novel findings highlight the importance of less frequently discussed musical attributes, such as musical structure, performer expression, and stage setting, as perceived across audio and visual modalities. Musicians are found to attribute emotion change to musical harmony, structure, and performance technique more than non-musicians. We suggest that accounting for such listener-informed music features can benefit MER in helping to address variability in emotion perception by providing reasons for listener similarities and idiosyncrasies.
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