MIDI2ScoreTransformer

Code for the ISMIR 2024 paper "End-to-end Piano Performance-MIDI to Score Conversion with Transformers"

Installation

The code is written in Python 3.11 and relies on the following packages

• everything mentioned in requirements.txt
• MuseScore: https://github.com/musescore/MuseScore (depending on your platform, please adjust the path in constants.py)

Due to delays and difficulties merging changes with upstream versions, we currently require installing custom versions of the following packages (will be done automatically with requirements.txt):

• music21: https://github.com/TimFelixBeyer/music21 (fixes tie-stripping and contains various other tweaks)
• score_transformer: https://github.com/TimFelixBeyer/ScoreTransformer (for score_similarity metrics and tokenization comparisons)

In addition, you must manually clone and install this package:

• muster: https://github.com/TimFelixBeyer/amtevaluation.github.io (fixes various memory leak issues of the original version)

Datasets

Please use this version of the ASAP-Dataset as it contains some fixes.

• ASAPDataset: https://github.com/TimFelixBeyer/ASAPDataset (contains a few fixes for the ASAP dataset, make sure you select the correct commit for reproducibility and place the asap-dataset folder into the data folder).
• ACPAS: https://cheriell.github.io/research/ACPAS_dataset/ (only download metadata_R.csv and metadata_S.csv, place them into a folder called ACPAS-dataset and put it into the data folder)

Afterwards, your data folder should look like this:

data
├── ACPAS-dataset
│   ├── metadata_R.csv
│   └── metadata_S.csv
└── asap-dataset

Setup (Inference)

1. Download the MIDI2ScoreTF.ckpt from GitHub ('Releases' section) and place it where you like.

Setup (Training)

1. Run dataset.py to preprocess the datasets and populate the cache.
2. Run chunker.py to create the beat-aligned chunks.
3. More instructions to follow