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MACHINE_LEARNING.md

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Machine Learning

Machine learning has been gaining traction in the audio industry lately. I don't know much about the topic myself, but I'll link some potentially useful resources here if you're interested.

  • 3Blue1Brown - Neural Networks - An excellent short series of YouTube videos explaining the basics of how machine learning actually works.
  • audioFlux - A deep learning tool library for audio and music analysis.
  • Deep Learning for Audio - A course that teaches how to use deep learning for audio processing.
  • nnAudio - An audio processing toolbox using the PyTorch convolutional neural network backend.
  • RTNeural - A fast neural inferencing library in C++ made specifically for audio plugins. Used by the Chowdhury DSP suite of plugins.
  • SmartCore - An advanced and comprehensive machine learning library written in the Rust programming language.

Open Source Projects

Some open source projects that make use of machine learning for audio.

  • AIDA-X - An amp model player that can load AI-trained models of music gear.
  • Chowdhury DSP - A suite of open source audio plugins. Many of them make use of machine learning.
  • DeepFilterNet - A low complexity speech enhancement/noise suppression framework.
  • GuitarML | (C++, [JUCE]) | - A collection of electric guitar effects that use neural network models to emulate real-world hardware.
  • NeuralNote - A state-of-the-art plugin that uses machine learning to convert audio to MIDI.
  • RNNoise - A noise suppression library based on a recurrent neural network.
  • Ultimate Vocal Remover - A state-of-the-art program that uses machine learning to separate vocals from a mix.