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.
Create a virtualenv and activate it. We need Python2 (and not Python3) because
pyoscis not compatible with Python3. This step is optional but recommended:
virtualenv --system-site-packages -p python2 venv source venv/bin/activate pip install -r requirements.txt
pip install pyosc.
Install Tensorflow (instructions here).
Install Magenta (instructions here).
Clone this repo.
Download Melody RNN
attention_rnnmodel here, and update the
Open SuperCollider, open
Psc2/server.scand run the main group (enclosed in parentheses).
From the root directory, run:
python setup.py install
Start the python server: