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Appl. Sci. 2017, 7(12), 1329; doi:10.3390/app7121329

Populating the Mix Space: Parametric Methods for Generating Multitrack Audio Mixtures

Acoustics Research Centre, School of Computing, Science and Engineering, University of Salford, Greater Manchester, Salford M5 4WT, UK
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Academic Editor: Tapio Lokki
Received: 31 October 2017 / Revised: 24 November 2017 / Accepted: 4 December 2017 / Published: 20 December 2017
(This article belongs to the Special Issue Sound and Music Computing)
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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. View Full-Text
Keywords: intelligent music production; music information retrieval; multitrack mixing; stereo panning; audio equalisation; tempo estimation; spectral centroid intelligent music production; music information retrieval; multitrack mixing; stereo panning; audio equalisation; tempo estimation; spectral centroid
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Wilson, A.; Fazenda, B.M. Populating the Mix Space: Parametric Methods for Generating Multitrack Audio Mixtures. Appl. Sci. 2017, 7, 1329.

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