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Beatle-Basslines

The project trains a Deep Learning model (including all data pre-processing) to generate basslines in the style of Paul McCartney from other tracks in a MIDI file. The code is easily modified to learn other instruments - e.g. vocal melodies or drums. Different real-world performers can be modeled by using a different dataset of MIDI files.

Features

  • Reads MIDI files (with properly labeled tracks) into a Pandas dataframe.
  • Transforms pianoroll data into ML-ready k-hot sequences of training, validation, and test data. Dimensionality is reduced with automatic note range clipping.
  • Play predicted and original sequence audio in-notebook for progress monitoring.
  • Model is currently a stacked BiLSTM.
  • Notebook includes all initialization to work from a repository clone in Google Drive.

Dependencies

  • Currently, TensorFlow/Keras is used for the modeling. This could be easily swapped for another tool.

  • The dataset is primarily based on a version of David W Barnes' MIDI library with relabeled and cleaned instrument tracks. I currently do not have permission to redistribute those files directly.

Licensing

This code is licensed under MIT license.