Abstract
Vacuum tube amplifiers present sonic characteristics often coveted by musicians, that are due to the distinct distortion of their circuits and accurately modeling such effects can be a challenging task. A recent rise in machine learning has lead to the ubiquity of neural networks in all fields including virtual analog modeling. This has lead to the appearance of a variety of architectures tailored to this task. We aim to provide an overview of the current state of the research in neural emulation of distortion circuits.
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Vanhatalo, T. et al. (2023). Neural Network-Based Virtual Analog Modeling. In: Legrand, P., et al. Artificial Evolution. EA 2022. Lecture Notes in Computer Science, vol 14091. Springer, Cham. https://doi.org/10.1007/978-3-031-42616-2_5
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