Abstract
Virtual analog modeling of audio effects consists of emulating the sound of an audio processor reference device. This digital simulation is normally done by designing mathematical models of these systems. It is often difficult because it seeks to accurately model all components within the effect unit, which usually contains various nonlinearities and time-varying components. Most existing methods for audio effects modeling are either simplified or optimized to a very specific circuit or type of audio effect and cannot be efficiently translated to other types of audio effects. Recently, deep neural networks have been explored as black-box modeling strategies to solve this task, i.e., by using only input–output measurements. We analyse different state-of-the-art deep learning models based on convolutional and recurrent neural networks, feedforward WaveNet architectures and we also introduce a new model based on the combination of the aforementioned models. Through objective perceptual-based metrics and subjective listening tests we explore the performance of these models when modeling various analog audio effects. Thus, we show virtual analog models of nonlinear effects, such as a tube preamplifier; nonlinear effects with memory, such as a transistor-based limiter and nonlinear time-varying effects, such as the rotating horn and rotating woofer of a Leslie speaker cabinet.
Highlights
Modeling of virtual analog audio effects is the process of emulating an audio effect unit and seeks to recreate the sound, behaviour and main perceptual features of an analog reference device [1]
We explored convolutional neural networks (CNN) to model linear effect units, such as equalization [6]; nonlinear effects with short-term memory, such as distortion, overdrive and amplifier emulation [7]
The training procedures were performed for each architecture and each modeling task: preamp corresponds to the vacuum-tube preamplifier, limiter to the transistor-based limiter amplifier, horn tremolo and horn chorale to the Leslie speaker rotating horn at fast and slow speeds, respectively, and woofer tremolo and woofer chorale to the rotating woofer at the corresponding speeds
Summary
Modeling of virtual analog audio effects is the process of emulating an audio effect unit and seeks to recreate the sound, behaviour and main perceptual features of an analog reference device [1]. Audio effect units are analog or digital signal processing systems that transform certain characteristics of the sound source. These transformations can be linear or nonlinear, time-invariant or time-varying and with short-term and long-term memory. Nonlinear audio effects: These effects are widely used by musicians and sound engineers and can be classified into two main types of effects: dynamic processors such as compressors or limiters; and distortion effects such as tube amplifiers [2]. The main sonic characteristic of these effects is due to their nonlinearities and the most common processors are overdrive, distortion pedals, tube amplifiers and guitar pickup emulators. Since a nonlinear system cannot be characterized by its impulse response, frequency response or transfer function [1], digital emulation of distortion effects have been extensively researched [39]
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