Neural Audio Funk - Generating Drum & Bass patterns with RAVE model in Pure Data

In this video, I'm showing the prototype of a patch setup that forces a RAVE model to generate Drum & Bass patterns using a sample based metro object in "the right" speed along with a sequencer component that retriggers noise seeds and signal generators in changing rhythmical patterns.

Additional drones come from a vschaos2 model that reacts on speed and patterns from the general setup.

The models used in this video have been trained on the "Black Plastics" series of tracks I've released in the past years. https://martsman.bandcamp.com

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All components used in this video can be found on GitHub: https://github.com/devstermarts/PD-co...

RAVE is "A variational autoencoder for fast and high-quality neural audio synthesis” created by Antoine Caillon and Philippe Esling of Artificial Creative Intelligence and Data Science (ACIDS) at IRCAM, Paris.

vschaos2 is a vintage-flavoured neural audio synthesis package by Axel Chemla Romeu Santos. It is based on unsupervised/ (semi-)supervised training of spectral information using variational auto-encoders.

RAVE on GitHub: https://github.com/acids-ircam/RAVE
nn~ on GitHub: https://github.com/acids-ircam/nn_tilde
vschaos2 on GitHub: https://github.com/acids-ircam/vschaos2

To train models on Colab or Kaggle, you can use these Jupyter notebooks i've set up: https://github.com/devstermarts/Noteb...