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Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

The Emotional Characteristics of Piano Sounds with Different Pitch and Dynamics

Chau, Chuck-Jee, Mo, Ronald and Horner, Andrew (2016) The Emotional Characteristics of Piano Sounds with Different Pitch and Dynamics. Journal of the Audio Engineering Society, 64 (11). pp. 918-932. ISSN 15494950

Item Type: Article

Abstract

The piano is an instrument extensively used in classical, jazz, and pop music since its broad pitch range and ample dynamic levels allow the instrument to become self-contained and versatile for various kinds of music. We conducted listening tests to compare the effects of pitch and dynamics on the emotional characteristics of isolated one-second piano sounds. Listeners compared the sounds pairwise over ten emotion categories. The results showed that all ten
emotional categories were significantly affected by pitch and nine of them by dynamics. In particular, the emotional characteristics Happy, Romantic, Comic, Calm, Mysterious, and Shy generally increased with pitch but sometimes decreased at the highest pitches. The characteristics Heroic, Angry, and Sad generally decreased with pitch. Scary was strong in the extreme low and high registers. In terms of dynamics, the results showed that the characteristics Heroic, Comic, Angry, and Scary were stronger for loud notes, while Romantic, Calm, Mysterious, Shy, and Sad were stronger for soft notes. Surprisingly, Happy was not affected by dynamics. These results help quantify the emotional characteristics of piano sounds.

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More Information

Depositing User: Ronald Mo

Identifiers

Item ID: 15802
Identification Number: https://doi.org/10.17743/jaes.2016.0049
ISSN: 15494950
URI: http://sure.sunderland.ac.uk/id/eprint/15802
Official URL: http://dx.doi.org/10.17743/jaes.2016.0049

Users with ORCIDS

ORCID for Ronald Mo: ORCID iD orcid.org/0000-0002-8746-2069

Catalogue record

Date Deposited: 20 Mar 2023 16:38
Last Modified: 20 Mar 2023 16:38

Contributors

Author: Ronald Mo ORCID iD
Author: Chuck-Jee Chau
Author: Andrew Horner

University Divisions

Faculty of Technology > School of Computer Science

Subjects

Performing Arts > Music
Computing

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