Mr Duncan Williams D.A.H.Williams@salford.ac.uk
Senior Lecturer
Investigating perceived emotional correlates of rhythmic density in algorithmic music composition
Williams, DAH; Nasuto, S; Kirke, A; Miranda, E; Daly, I; Hallowell, J; Weaver, J; Malik, A; Roesch, E; Hwang, F
Authors
S Nasuto
A Kirke
E Miranda
I Daly
J Hallowell
J Weaver
A Malik
E Roesch
F Hwang
Abstract
Affective algorithmic composition is a growing field that combines perceptually motivated affective computing strategies with novel music generation. This article presents work toward the development of one application. The long-term goal is to develop a responsive and adaptive system for inducing affect that is both controlled and validated by biophysical measures. Literature documenting perceptual responses to music identifies a variety of musical features and possible affective correlations, but perceptual evaluations of these musical features for the purposes of inclusion in a music generation system are not readily available. A discrete feature, rhythmic density (a function of note duration in each musical bar, regardless of tempo), was selected because it was shown to be well-correlated with affective responses in existing literature. A prototype system was then designed to produce controlled degrees of variation in rhythmic density via a transformative algorithm. A two-stage perceptual evaluation of a stimulus set created by this prototype was then undertaken. First, listener responses from a pairwise scaling experiment were analyzed via Multidimensional Scaling Analysis (MDS). The statistical best-fit solution was rotated such that stimuli with the largest range of variation were placed across the horizontal plane in two dimensions. In this orientation, stimuli with deliberate variation in rhythmic density appeared farther from the source material used to generate them than from stimuli generated by random permutation. Second, the same stimulus set was then evaluated according to the order suggested in the rotated two-dimensional solution in a verbal elicitation experiment. A Verbal Protocol Analysis (VPA) found that listener perception of the stimulus set varied in at least two commonly understood emotional descriptors, which might be considered affective correlates of rhythmic density. Thus, these results further corroborate previous studies wherein musical parameters are monitored for changes in emotional expression and that some similarly parameterized control of perceived emotional content in an affective algorithmic composition system can be achieved and provide a methodology for evaluating and including further possible musical features in such a system. Some suggestions regarding the test procedure and analysis techniques are also documented here.
Citation
Williams, D., Nasuto, S., Kirke, A., Miranda, E., Daly, I., Hallowell, J., …Hwang, F. (2015). Investigating perceived emotional correlates of rhythmic density in algorithmic music composition. ACM transactions on applied perception, 12(3), 1-21. https://doi.org/10.1145/2749466
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 1, 2015 |
Publication Date | Jul 28, 2015 |
Deposit Date | Dec 12, 2019 |
Journal | ACM Transactions on Applied Perception |
Print ISSN | 1544-3558 |
Electronic ISSN | 1544-3965 |
Publisher | Association for Computing Machinery (ACM) |
Volume | 12 |
Issue | 3 |
Pages | 1-21 |
DOI | https://doi.org/10.1145/2749466 |
Publisher URL | https://doi.org/10.1145/2749466 |
Related Public URLs | https://tap.acm.org/ |
You might also like
Timbral Metrics for Analysis of Metal Production: Then, Now and What Next?
(2023)
Book Chapter
Sonic enhancement of virtual exhibits
(2022)
Journal Article
What our bodies tell us about noise
(2022)
Journal Article
Psychophysiological approaches to sound and music in games
(2021)
Book Chapter
Downloadable Citations
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search