TY - GEN
T1 - Psychophysiological measures of emotional response to romantic orchestral music and their musical and acoustic correlates
AU - Trochidis, Konstantinos
AU - Sears, David
AU - Trân, Diêu Ly
AU - McAdams, Stephen
PY - 2013
Y1 - 2013
N2 - This paper examines the induction of emotions while listening to Romantic orchestral music. The study seeks to explore the relationship between subjective ratings of felt emotion and acoustic and physiological features. We employed 75 musical excerpts as stimuli to gather responses of excitement and pleasantness from 20 participants. During the experiments, physiological responses of the participants were measured, including blood volume pulse (BVP), skin conductance (SC), respiration rate (RR) and facial electromyography (EMG). A set of acoustic features was derived related to dynamics, harmony, timbre and rhythmic properties of the music stimuli. Based on the measured physiological signals, a set of physiological features was also extracted. The feature extraction process is discussed with particular emphasis on the interaction between acoustical and physiological parameters. Statistical relations among audio, physiological features and emotional ratings from psychological experiments were systematically investigated. Finally, a forward step-wise multiple linear regression model (MLR) was employed using the best features, and its prediction efficiency was evaluated and discussed. The results indicate that merging acoustic and physiological modalities substantially improves prediction of participants' ratings of felt emotion compared to the results using the modalities in isolation.
AB - This paper examines the induction of emotions while listening to Romantic orchestral music. The study seeks to explore the relationship between subjective ratings of felt emotion and acoustic and physiological features. We employed 75 musical excerpts as stimuli to gather responses of excitement and pleasantness from 20 participants. During the experiments, physiological responses of the participants were measured, including blood volume pulse (BVP), skin conductance (SC), respiration rate (RR) and facial electromyography (EMG). A set of acoustic features was derived related to dynamics, harmony, timbre and rhythmic properties of the music stimuli. Based on the measured physiological signals, a set of physiological features was also extracted. The feature extraction process is discussed with particular emphasis on the interaction between acoustical and physiological parameters. Statistical relations among audio, physiological features and emotional ratings from psychological experiments were systematically investigated. Finally, a forward step-wise multiple linear regression model (MLR) was employed using the best features, and its prediction efficiency was evaluated and discussed. The results indicate that merging acoustic and physiological modalities substantially improves prediction of participants' ratings of felt emotion compared to the results using the modalities in isolation.
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U2 - 10.1007/978-3-642-41248-6_3
DO - 10.1007/978-3-642-41248-6_3
M3 - Conference contribution
AN - SCOPUS:84885073853
SN - 9783642412479
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 44
EP - 57
BT - From Sounds to Music and Emotions - 9th International Symposium, CMMR 2012, Revised Selected Papers
T2 - 9th International Symposium on Computer Music Modeling and Retrieval, CMMR 2012
Y2 - 19 June 2012 through 22 June 2012
ER -