Variation in multitrack mixes : analysis of low-level audio signal features

Wilson, AD; Fazenda, BM

Abstract

To further the development of intelligent music production tools, towards generating mixes
that would realistically be created by a human mix-engineer, it is important to understand what
kind of mixes can be created, and are typically created, by human mix-engineers. This paper
presents an analysis of 1501 mixes, over 10 different songs, created by mix-engineers. The
primary dimensions of variation in the full dataset of mixes were ‘amplitude’, ‘brightness’,
‘bass’ and ‘width’, as determined by feature-extraction and subsequent principal component
analysis. The distribution of representative features approximated a normal distribution and
this is then used to obtain general trends and tolerance bounds for these features. The results
presented here are useful as parametric guidance for intelligent music production systems.

• Journal Article Type: Article
• Acceptance Date: Jun 17, 2016
• Online Publication Date: Aug 11, 2016
• Publication Date: Aug 11, 2016
• Deposit Date: Jun 24, 2016
• Publicly Available Date: Sep 5, 2016
• Journal: Journal of the Audio Engineering Society
• Print ISSN: 1549-4950
• Publisher: Audio Engineering Society
• Volume: 64
• Issue: 7/8
• Pages: 466-473
• DOI: https://doi.org/10.17743/jaes.2016.0029
• Publisher URL: http://dx.doi.org/10.17743/jaes.2016.0029
• Related Public URLs: http://www.aes.org/journal/