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.