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Schedule as of Oct 11, 2022 - subject to change

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Thursday, October 20 • 2:00pm - 2:20pm
Approximating Ballistics in a Differentiable Dynamic Range Compressor

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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.

Speakers
avatar for Joseph Colonel

Joseph Colonel

Centre for Digital Music , Queen Mary University of London
Joseph T Colonel is a final year PhD student in the Centre for Digital Music at Queen Mary University of London. His work focuses on applying machine learning and neural networks to music production behavior modelling. JT held an internship at Soundwide working on differentiable digital... Read More →
avatar for Joshua Reiss

Joshua Reiss

AES President, Queen Mary University of London
Josh Reiss is Professor of Audio Engineering with the Centre for Digital Music at Queen Mary University of London. He has published more than 200 scientific papers (including over 50 in premier journals and 6 best paper awards) and co-authored two books. His research has been featured... Read More →


Thursday October 20, 2022 2:00pm - 2:20pm EDT
2D02/03