Quantitative Analysis of the Im pact of Mixing on Perceived Emotion of Soundscape Recordings
Paper in proceeding, 2018

Sound designers routinely mix source soundscape recordings. Previous studies have shown that people agree with each other on the perceived valence and arousal for soundscape recordings. This study investigates whether
we can compute the perceived emotion of the mixed soundscape recordings based on the perceived emotion of source soundscape recordings. We discovered quantifiable trends in the effect of mixing on the perceived emotion of soundscape recordings. Regression analysis based on the trajectory observation resulted in coefficients with high R2 values. We found that the change of loudness of a source soundscape recording had an influence on its weight on the perceived emotion of mixed-soundscape recordings. Our visual analysis of the center of mass data
plots found the specific patterns of the perceived emotion
of the source soundscape recordings that belong to different soundscape categories and the perceived emotion of the mix. We also found that when the difference in valence/arousal between two source soundscape recordings is larger than a given threshold, it is highly likely that the valence/arousal of the mix is in between the valence/arousal of two source soundscape recordings.

affect estimation

machine learning

sound and music computing

Author

Jianyu Fan

Miles Thorogood

University of British Columbia (UBC)

Kivanc Tatar

Data Science and AI

Philippe Pasquier

Simon Fraser University

Proceedings of the Sound and Music Computing Conferences

25183672 (eISSN)

Vol. 15
978-9963-697-30-4 (ISBN)

Sound and Music Computing
Limassol, Cyprus,

Subject Categories

Media and Communication Technology

More information

Created

2/16/2024