ORIGINAL RESEARCH article

Front. Signal Process.

Sec. Audio and Acoustic Signal Processing

Volume 5 - 2025 | doi: 10.3389/frsip.2025.1580395

Differentiable Black-box and Gray-box Modeling of Nonlinear Audio Effects

Provisionally accepted
Marco  ComunitàMarco Comunità*Christian  J SteinmetzChristian J SteinmetzJoshua  ReissJoshua Reiss*
  • Queen Mary University of London, London, United Kingdom

The final, formatted version of the article will be published soon.

Audio effects are extensively used at every stage of audio and music content creation. The majority of differentiable audio effects modeling approaches fall into the black-box or gray-box paradigms; and most models have been proposed and applied to nonlinear effects like guitar amplifiers, overdrive, distortion, fuzz and compressor. Although a plethora of architectures have been introduced for the task at hand there is still lack of understanding on the state of the art, since most publications experiment with one type of nonlinear audio effect and a very small number of devices.In this work we aim to shed light on the audio effects modeling landscape by comparing blackbox and gray-box architectures on a large number of nonlinear audio effects, identifying the most suitable for a wide range of devices. In the process, we also: introduce time-varying gray-box models and propose models for compressor, distortion and fuzz, publish a large dataset for audio effects research-ToneTwist AFx 1 -that is also the first open to community contributions, evaluate models on a variety of metrics and conduct extensive subjective evaluation. Code 2 and supplementary material 3 are also available.

Keywords: Audio effects, black-box modeling, Gray-box modeling, neural networks, Differentiable DSP

Received: 20 Feb 2025; Accepted: 23 Jun 2025.

Copyright: © 2025 Comunità, Steinmetz and Reiss. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Marco Comunità, Queen Mary University of London, London, United Kingdom
Joshua Reiss, Queen Mary University of London, London, United Kingdom

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