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computer music modeling and retrieval | 2012

Psychophysiological Measures of Emotional Response to Romantic Orchestral Music and Their Musical and Acoustic Correlates

Konstantinos Trochidis; David R. W. Sears; Diêu-Ly Trân; Stephen McAdams

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.


Journal of New Music Research | 2018

Simulating melodic and harmonic expectations for tonal cadences using probabilistic models

David R. W. Sears; Marcus T. Pearce; William E. Caplin; Stephen McAdams

Abstract This study examines how the mind’s predictive mechanisms contribute to the perception of cadential closure during music listening. Using the Information Dynamics of Music model (or IDyOM) to simulate the formation of schematic expectations—a finite-context (or n-gram) model that predicts the next event in a musical stimulus by acquiring knowledge through unsupervised statistical learning of sequential structure—we predict the terminal melodic and harmonic events from 245 exemplars of the five most common cadence categories from the classical style. Our findings demonstrate that (1) terminal events from cadential contexts are more predictable than those from non-cadential contexts; (2) models of cadential strength advanced in contemporary cadence typologies reflect the formation of schematic expectations; and (3) a significant decrease in predictability follows the terminal note and chord events of the cadential formula.


Psychophysiology | 2016

Psychophysiological responses to auditory change

Lorraine Chuen; David R. W. Sears; Stephen McAdams

A comprehensive characterization of autonomic and somatic responding within the auditory domain is currently lacking. We studied whether simple types of auditory change that occur frequently during music listening could elicit measurable changes in heart rate, skin conductance, respiration rate, and facial motor activity. Participants heard a rhythmically isochronous sequence consisting of a repeated standard tone, followed by a repeated target tone that changed in pitch, timbre, duration, intensity, or tempo, or that deviated momentarily from rhythmic isochrony. Changes in all parameters produced increases in heart rate. Skin conductance response magnitude was affected by changes in timbre, intensity, and tempo. Respiratory rate was sensitive to deviations from isochrony. Our findings suggest that music researchers interpreting physiological responses as emotional indices should consider acoustic factors that may influence physiology in the absence of induced emotions.


Music Perception: An Interdisciplinary Journal | 2014

Perceiving the Classical Cadence

David R. W. Sears; William E. Caplin; Stephen McAdams


international conference on acoustics, speech, and signal processing | 2018

A Large-Scale Study Of Language Models for Chord Prediction

Filip Korzeniowski; David R. W. Sears; Gerhard Widmer


arXiv: Sound | 2018

Psychological constraints on string-based methods for pattern discovery in polyphonic corpora.

David R. W. Sears; Gerhard Widmer


Archive | 2018

Evaluating language models of tonal harmony.

David R. W. Sears; Filip Korzeniowski; Gerhard Widmer


international symposium/conference on music information retrieval | 2017

Modeling Harmony with Skip-Grams.

David R. W. Sears; Andreas Arzt; Reinhard Sonnleitner; Gerhard Widmer


Archive | 2017

Automatic estimation of harmonic tension by distributed representation of chords.

Ali Nikrang; David R. W. Sears; Gerhard Widmer


Archive | 2017

What were you expecting? Using Expectancy Features to Predict Expressive Performances of Classical Piano Music.

Carlos Eduardo Cancino Chacón; Maarten Grachten; David R. W. Sears; Gerhard Widmer

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Gerhard Widmer

Johannes Kepler University of Linz

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Filip Korzeniowski

Johannes Kepler University of Linz

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Marcus T. Pearce

Queen Mary University of London

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Andreas Arzt

Johannes Kepler University of Linz

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Carlos Eduardo Cancino Chacón

Austrian Research Institute for Artificial Intelligence

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Maarten Grachten

Johannes Kepler University of Linz

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