JOINT ESTIMATION OF FADER AND EQUALIZER GAINS OF DJ MIXERS USING CONVEX OPTIMIZATION

Abstract

Disc jockeys (DJs) use audio effects to make a smooth transition from one song to another. There have been attempts to computationally analyze the creative process of seamless mixing. However, only a few studies estimated fader or equalizer (EQ) gains controlled by DJs. In this study, we propose a method that jointly estimates time-varying fader and EQ gains so as to reproduce the mix from individual source tracks. The method approximates the equalizer filters with a linear combination of a fixed equalizer filter and a constant gain to convert the joint estimation into a convex optimization problem. For the experiment, we collected a new DJ mix dataset that consists of 5, 040 real-world DJ mixes with 50, 742 transitions, and evaluated the proposed method with a mix reconstruction error. The result shows that the proposed method estimates the time-varying fader and equalizer gains more accurately than existing methods and simple baselines.