Basically, given that nonlinear audio effects are widely used by musicians and sound engineers and taking into account that most existing methods for nonlinear modeling are often either simplified or optimized to a very specific circuit. In this work, we introduce a general-purpose deep learning architecture for generic black-box modeling of nonlinear and linear audio effects.
We show the model performing nonlinear modeling for distortion, overdrive, amplifier emulation and combination of linear and nonlinear audio effects.
You can listen to some audio samples here.
Details about the presentation:
Session: AASP-L6: Music Signal Analysis, Processing and Synthesis
Location: Meeting Room 1
Time: Thursday, May 16, 09:20 – 09:40 (Approximate)
Title: Modeling Nonlinear Audio Effects With End-to-end Deep Neural Networks
Authors: Marco A. Martinez Ramirez, Joshua D. Reiss