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R-VAE

Rhythm generator using Variational Autoencoder(VAE) as a Max for Live (M4L) plugin

This is a fork of M4L.RhythmVAE by Nao Tokui, modded and extended to support simple and compound meter rhythms, with minimal amount of training data.

Similarly to RhythmVAE, the goal of R-VAE is the exploration of latent spaces of musical rhythms. Unlike most previous work in rhythm modeling, R-VAE can be trained with small datasets, enabling rapid customization and exploration by individual users. R-VAE employs a data representation that encodes simple and compound meter rhythms. To the best of our knowledge, this is the first time that a network architecture has been used to encode rhythms with these characteristics, which are common in some modern popular music genres.

Improvements

  • Modeling of simple and compound meter rhythms, achieved by improving the resolution from 4 to 24 ppqn (pulser per quarter note)
  • Playback head latent space can be controlled from any mappable parameter in Ableton Live
  • Reset button allows to reset the sequence to 1.1.0
  • If little training data is provided, the data is duplicated to achieve a minimum number of clips so that they can be processed by the network, and the loss decreases
  • Synchronization to Ableton Live and Max Transport Control is improved
  • Shuffle variable was refactored
  • Toggle for fix or variable velocity was added
  • Implement a hack to avoid inconsistencies between versions of tfjs_binding.node under different folder structures. See this
  • Models of footwork and trap learned with as little as 12 clips can be downloaded from here
  • A 30 * 30 matrix is generated based on the latent space. That is, the continuous latent space is sampled and the sequences of onsets per instrument are stored in a matrix.
  • XY grid receives and sends OSC messages. The ports used are the Wekinator defaults (12000 and 6448)

Generating a M4L device

  • Make sure to open the *.maxproj project file. Then in the Project Inspector set Max for Live Device Type to “MIDI.“
  • Choose Export Max for Live Device
  • Don't forget to add to the Search Paths in Project Settings everything you need to include in your distribution (e.g., .maxpat files, .js files, node modules, etc.)
  • Get your M4L device from the /release folder
  • Play!

Requirements

  • macOS >= 10.12.x (due to clock_gettime requirements of libtensorflow)