![Sample our Engineering & Technology journals, sign in here to start your access, latest two full volumes FREE to you for 14 days]({"type":"image" , "src" : "/sda/5933/TOC-Subject-Sample-2021-Engineering-Tech.jpg"})
Abstract
Advances in the fields of data processing and sonification have been applied to transcribe a variety of visual experiences into an auditory format. Although image sonification examples exist, the application of these principles to visual art has not been examined thoroughly. We sought to develop and evaluate a set of guidelines for the sonification of visual artworks. Through conducting expert interviews (N = 11), we created an initial sonification algorithm that accounts for art style, lightness, and color diversity to modulate the sonified output in terms of tempo and pitch. This algorithm was evaluated through user evaluations (N = 22). User study responses supported expert interview findings, the notion that sonification can be designed to match the experience of viewing an artwork, and showed interesting interaction effects among art styles, visual components, and musical parameters. We suggest the proposed guidelines can augment visitor experiences at art exhibits and provide the basis for further experimentation.
Disclosure statement
No potential conflict of interest was reported by the author(s).
Additional information
Notes on contributors
Chihab Nadri
Chihab Nadri is a Ph.D. candidate and lab manager of the Mind Music Machine Lab. His research interests include Automotive Display Design, Music Computing, and Human-Computer Interaction.
Chairunisa Anaya
Chairunisa Anaya is a recent graduate from Virginia Tech with a major in Industrial and Systems Engineering and a minor in Statistics. She was an undergraduate researcher at the Mind Music Machine Lab.
Shan Yuan
Shan Yuan is a recent graduate from Virginia Tech with a major in Industrial and Systems Engineering. She was an undergraduate researcher at the Mind Music Machine Lab and worked on artwork sonification and robot theater projects.
Myounghoon Jeon
Myounghoon Jeon is an Associate Professor of Industrial and Systems Engineering and Computer Science at Virginia Tech and director of the Mind Music Machine Lab. His research focuses on emotions and sound in the areas of Automotive User Experiences, Assistive Robotics, and Arts in XR Environments.