Populating the mix space : parametric methods for
generating multitrack audio mixtures

Wilson, AD; Fazenda, BM

Abstract

The creation of multitrack mixes by audio engineers is a time-consuming activity and creating high-quality mixes requires a great deal of knowledge and experience. Previous studies on the perception of music mixes have been limited by the relatively small number of human-made mixes analysed. This paper describes a novel mix-space, a parameter space which contains all possible mixes using a finite set of tools, as well as methods for the parametric generation of artificial mixes in this space. Mixes that use track gain, panning and equalisation are considered. This allows statistical methods to be used in the study of music mixing practice, such as Monte Carlo simulations or population-based optimisation methods. Two applications are described: an investigation into the robustness and accuracy of tempo-estimation algorithms and an experiment to estimate distributions of spectral centroid values within sets of mixes. The potential for further work is also described.

• Journal Article Type: Article
• Acceptance Date: Dec 4, 2017
• Online Publication Date: Dec 20, 2017
• Publication Date: Dec 20, 2017
• Deposit Date: Dec 12, 2017
• Publicly Available Date: Jan 4, 2018
• Journal: Applied Sciences
• Electronic ISSN: 2076-3417
• Publisher: MDPI
• Volume: 7
• Issue: 12
• Pages: 1329
• DOI: https://doi.org/10.3390/app7121329
• Publisher URL: http://dx.doi.org/10.3390/app7121329
• Related Public URLs: http://www.mdpi.com/journal/applsci