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Evaluation of Tube Screamer Simulation using Machine Learning
In this paper a comparison between the original analog circuit that represents the ground truth and the simulation of nonlinear analog circuits using neural networks is performed. Traditionally the white box approach has provided some good results in terms of accuracy but implies an important computational demand to emulate digital audio effects (DAFx). Newer approaches using neural networks provide a black box approach that can be more efficient, accessible and potentially obtain similar ordoi:10.5281/zenodo.7116346 fatcat:zuosjnljqbfwrgmo3typr5j4jq