This paper presents MixViz, a real-time audio production tool that helps users visually detect and eliminate masking in audio mixes. This work adapts the Glasberg and Moore time-varying Model of Loudness and Partial Loudness to analyze multiple audio tracks for instances of masking. We extend the Glasberg and Moore model to allow it to account for spatial release from masking effects. Each audio track is assigned a hue and visualized in a 2-dimensional display where the horizontal dimension is spatial location (left to right) and the vertical dimension is frequency. Masking between tracks is indicated via a change of color. The user can quickly drag and drop tracks into and out of the mix visualization to observe the effects on masking. This lets the user intuitively see which tracks are masked in which frequency ranges and take action accordingly. This tool has the potential to both make mixing easier for novices and improve the efficiency of expert mixers.
Ford, Jon; Cartwright, Mark; Pardo, Bryan
Affiliation: Northwestern University, Evanston, IL, USA
AES Convention: 139 (October 2015) Paper Number: 9443
Publication Date: October 23, 2015
Subject: Recording and Production
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