Psc2

Psc2 combines the worlds of jazz, rock, classical music, and artificial intelligence via original compositions and arrangements.

the compositions are built around the interplay of jazz harmonies, complex rhythms and extensive improvisation; many of them are composed in the "long-form" compositional style of classical music.

the arrangements take well-known songs from pop, rock and jazz and re-build them in a manner similar to our original compositions. the arrangements include songs by michael jackson, guns n' roses, silvio rodriguez, duke ellington and others.

psc is a señor swesearcher in google brain, and is experimenting with using machine learning models (including generative models for music) as part of the live performance. most of the code used will be available in this repo.

the white paper explaining the solo setting is available here.

Installation

1. Install SuperCollider

2. Clone this repo.

3. Create a virtualenv and activate it. We need Python2 (and not Python3) because pyosc is not compatible with Python3. This step is optional but recommended:

   virtualenv --system-site-packages -p python2 venv
   source venv/bin/activate
   cd Psc2
   pip install -r requirements.txt
   

   If the last command does not work, then:

   1. pip install absl-py

   2. pip install pyosc.

   3. pip install tensorflow Full instructions here.

   4. pip install magenta Full instructions here.

4. Download Melody RNN attention_rnn model here, and update the base_models_path parameter in Psc2/modes/mlsplainer.py.

5. Download DrumKit RNN model (for NeurIPS demo) here.

6. Open SuperCollider, open Psc2/server.sc and run the main group (enclosed in parentheses).

7. From the root directory, run:

   python setup.py install
   

8. Start the python server:

   python Psc2/server.py