Timmers, R. orcid.org/0000-0002-1981-0834 (2020) Analyzing relationships between color, emotion and music using Bayes' rule in Bach's Well-Tempered Clavier Book 1. International Journal of Music Science, Technology and Art, 2 (1). pp. 40-47. ISSN 2612-2146
Abstract
A probabilistic approach to the perception of emotion and color in music is proposed and the application of Bayes' rule to predict previously collected data is investigated. Specifically, performances of Bach's Well-Tempered Clavier Book I were analyzed in terms of mode, tempo and intensity. Estimates of probabilistic relationships between features and emotion dimensions were used to predict listeners' associations with the music in terms of emotion and color. Predictions were particularly successful for emotion perception, although color was also reliably predicted for 14 out of 24 Preludes. If color was predicted directly from emotion perception, reliable prediction increased to 18 out of 24 Preludes.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Author et al., licensed to IJIEST. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited. |
Keywords: | Bayesian probability; Emotion; Music perception; Synesthesia |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Arts and Humanities (Sheffield) > Department of Music (Sheffield) |
Funding Information: | Funder Grant number Worldwide Universities Network Research Mobility Program (RMP) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 03 Jul 2020 07:36 |
Last Modified: | 03 Jul 2020 07:36 |
Published Version: | https://www.ijmsta.com/archive_card.php?id=61 |
Status: | Published |
Publisher: | Studio Musica Press |
Refereed: | Yes |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:162728 |