We present a lightweight method of reverse engineering distortion effects using Wiener-Hammerstein models implemented in a differentiable framework. The Wiener-Hammerstein models are formulated using graphic equalizer pre-emphasis and de-emphasis filters and a parameterized waveshaping function. Several parameterized waveshaping functions are proposed and evaluated. The performance of each method is measured both objectively and subjectively on a dataset of guitar distortion emulation software plugins and guitar audio samples.

Authors: Colonel, Joseph T.; Comunità, Marco; Reiss, Joshua
Affiliations: Queen Mary University of London, UK; Queen Mary University of London, UK; Queen Mary University of London, UK(See document for exact affiliation information.)
AES Convention: 153 (October 2022) Paper Number: 10626
Publication Date: October 19, 2022 Import into BibTeX
Subject: Signal Processing
Permalink: https://www.aes.org/e-lib/browse.cfm?elib=21955

Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!

This paper costs $33 for non-members and is free for AES members and E-Library subscribers.

Learn more about the AES E-Library

E-Library Location:   /conv/153/10626.pdf

Start a discussion about this Signal Processing!