Arranger

Directory structure

├─ analysis         Notebooks for analysis
├─ scripts          Scripts for running experiments
├─ models           Pretrained models
└─ arranger         Main Python module
   ├─ config.yaml   Configuration file
   ├─ data          Code for collecting and processing data
   ├─ common        Most-common algorithm
   ├─ zone          Zone-based algorithm
   ├─ closest       Closest-pitch algorithm
   ├─ lstm          LSTM model
   └─ transformer   Transformer model

Prerequisites

You can install the dependencies by running pipenv install (recommended) or python3 setup.py install -e .. Python>3.6 is required.

Data preparation

Please follow the instruction in arranger/data/README.md.

Models

• LSTM model
  • arranger/lstm/train.py: Train the LSTM model
  • arranger/lstm/infer.py: Infer with the LSTM model
• Transformer model
  • arranger/transformer/train.py: Train the Transformer model
  • arranger/transformer/infer.py: Infer with the Transformer model

Baseline algorithms

• Most-common algorithm
  • arranger/common/learn.py: Learn the most common label
  • arranger/common/infer.py: Infer with the most-common algorithm
• Zone-based algorithm
  • arranger/zone/learn.py: Learn the optimal zone setting
  • arranger/zone/infer.py: Infer with the zone-based algorithm
• Closest-pitch algorithm
  • arranger/closest/infer.py: Infer with the closest-pitch algorithm
• MLP model
  • arranger/mlp/train.py: Train the MLP model
  • arranger/mlp/infer.py: Infer with the MLP model

Configuration

In arranger/config.yaml, you can configure the MIDI program numbers used for each track in the sample files generated. You can also configure the color of the generated sample piano roll visualization.