Corpus ID: 167217646

SignalTrain: Profiling Audio Compressors with Deep Neural Networks

  title={SignalTrain: Profiling Audio Compressors with Deep Neural Networks},
  author={S. Hawley and Benjamin Colburn and S. I. Mimilakis},
  • S. Hawley, Benjamin Colburn, S. I. Mimilakis
  • Published 2019
  • Computer Science, Engineering
  • ArXiv
  • In this work we present a data-driven approach for predicting the behavior of (i.e., profiling) a given non-linear audio signal processing effect (henceforth "audio effect. [...] Key Method Compressors were chosen because they are a widely used and important set of effects and because their parameterized nonlinear time-dependent nature makes them a challenging problem for a system aiming to profile "general" audio effects. Results from our experimental procedure show that the primary functional and auditory…Expand Abstract
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