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MIDIformers

Table of Contents

DeepMixer

The project involves the usage of the open-source MusicBERT model to perform mask prediction tasks for MIDI task with customizability.

Installation 

git clone https://github.com/tripathiarpan20/midiformers.git
cd midiformers/DeepMixer/models/musicbert
./setup.sh

Notebook

The live version of Colab notebook utilising the scripts in DeepMixer/models/musicbert can be accessed from this link :

Image

The notebook supports customisability on top of the original MusicBERT codebase, like masking chosen percentage of random notes from either whole MIDI stream/ notes from selected instruments based on user preference.

Other features include:

  • Option to leaving notes from the beginning min_bar_mask masks out of the masking pool to provide more initial context for mask prediction.
  • Prediction modes with trade-off between speed and quality of predictions.
  • Sampling strategies like Temperature, Top-k and Nuclues (Top-p) added for mask predictions.
  • Filtering invalid prediction for more consistent results.
  • Song segment selection and multi-program/ins masking.

Output samples

Some of the samples from the above notebook along with the reference pieces can be found in a Drive folder , the songs are copyrighted by the respective owners.

A few of our favorites are embedded below:

  • Shock (Attack on Titan):
    • Original & Remix:
Shock_-_Attack_On_Titan.mp4
Shock_-_Attack_On_Titan_program0_40percentmaskpred.mp4
  • Bohemian Rhapsody (Queen):
    • Original & Remix:
BohemianRhapsody.mp4
bohemian_ckpt2_program128_92percentmaskpred_minbarmask4.mp4
  • Unforgiven 2 (Metallica):
    • Original & Remix:
Unforgiven2_track_filtered.1.mp4
Unforgiven2_program26_75percentmaskpred_minbarmask4_Vanilla.1.mp4

Support

There are many ways to support a project - starring⭐️ the GitHub repo is just one.