Computational and Psycho-Physiological Investigations of Musical Emotions

Abstract

The ability of music to stir human emotions is a well known fact (Gabrielsson & Lindstrom.2001). However, the manner in which music contributes to those experiences remainsobscured. One of the main reasons is the large number of syndromes that characteriseemotional experiences. Another is their subjective nature: musical emotions can beaffected by memories, individual preferences and attitudes, among other factors (Scherer& Zentner, 2001). But can the same music induce similar affective experiences in alllisteners, somehow independently of acculturation or personal bias? A considerablecorpus of literature has consistently reported that listeners agree rather strongly aboutwhat type of emotion is expressed in a particular piece or even in particular moments orsections (Juslin & Sloboda, 2001). Those studies suggest that music features encodeimportant characteristics of affective experiences, by suggesting the influence of variousstructural factors of music on emotional expression. Unfortunately, the nature of theserelationships is complex, and it is common to find rather vague and contradictorydescriptions.This thesis presents a novel methodology to analyse the dynamics of emotionalresponses to music. It consists of a computational investigation, based on spatiotemporalneural networks sensitive to structural aspects of music, which "mimic" human affectiveresponses to music and permit to predict new ones. The dynamics of emotionalresponses to music are investigated as computational representations of perceptualprocesses (psychoacoustic features) and self-perception of physiological activation(peripheral feedback). Modelling and experimental results provide evidence suggestingthat spatiotemporal patterns of sound resonate with affective features underlyingjudgements of subjective feelings. A significant part of the listener's affective responseis predicted from the a set of six psychoacoustic features of sound - tempo, loudness,multiplicity (texture), power spectrum centroid (mean pitch), sharpness (timbre) andmean STFT flux (pitch variation) - and one physiological variable - heart rate. This workcontributes to new evidence and insights to the study of musical emotions, with particularrelevance to the music perception and emotion research communities.

Date of Award	2008
Original language	English
Awarding Institution	University of Plymouth
Supervisor	Angelo Cangelosi (Director of Studies (First Supervisor)) & Guido Bugmann (Other Supervisor)