Experiments for Coupled Recurrent Models for Polyphonic Music Composition.
Corresponding author: John Thickstun. University of Washington
This repository contains code for the experiments discussed in Coupled Recurrent Models for Polyphonic Music Composition.
Included are notebooks for reproducing the single-part and multi-part experiments presented in Table 3 and Table 4 respectively.
For examples of how to generate output from the model in audio, kern, and midi representations, see sampling.ipynb. A pre-trained model is included for the multipart6 architecture.
-
PyTorch (tested with v1.5.0)
-
Jupyter (tested with v4.4.0)
-
NumPy (tested with v1.18.4)
-
SciPy (tested with v1.4.1)
-
Mido (tested with v1.2.9)
-
Scikit-learn (tested with v0.22.2)
-
Matplotlib (tested with v2.1.2)
To reference this work, please cite
@article{thickstun2019coupled,
author = {Thickstun, John and Harchaoui, Zaid and Foster, Dean P and Kakade, Sham M},
title = {Coupled Recurrent Models for Polyphonic Music Composition},
journal = {International Society for Music Information Retrieval},
year = {2019},
}