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Approximating Ballistics in a Differentiable Dynamic Range Compressor

Authors: Colonel, Joseph, T.; Reiss, Joshua D.

AES Convention 153 · Paper 33 · October 2022

Abstract

We present a dynamic range compressor with ballistics implemented in a differentiable framework that can be used for differentiable digital signal processing tasks. This compressor can update the values of its threshold, compression ratio, knee width, makeup gain, attack time, and release time using stochastic gradient descent and backpropagation techniques. The performance of this technique is evaluated on a reverse engineering of audio effects task, in which the parameter settings of a dynamic range compressor are inferred from a dry and wet pair of audio samples. Techniques for initializing the parameter estimates in this reverse engineering task are outlined and discussed.

Details

Published in
AES Convention 153
AES Convention
153
Paper number
33
Publication date
October 6, 2022
Session subject
Applications in Audio
Affiliation
Queen Mary University of London, UK; Queen Mary University of London, UK (See document for exact affiliation information.)
Type
Express Paper