Using Keras & Theano for deep learning driven jazz generation
I built deepjazz in 36 hours for HackPrinceton, Spring 2016. It uses Keras & Theano, two deep learning libraries, to generate jazz music. Specifically, it builds a two-layer LSTM , learning from the given MIDI file. It uses deep learning, the AI tech that powers Google’s AlphaGo and IBM’s Watson , to make music — something that’s considered as deeply human .
Check out deepjazz’s music on SoundCloud !
Run on CPU with command:
python generator.py [# of epochs]
Run on GPU with command:
THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python generator.py [# of epochs]
preprocess.py must be modified to work with other MIDI files (the relevant "melody" MIDI part needs to be selected). The ability to handle this natively is a planned feature.
This project develops a lot of preprocessing code (with permission) from Evan Chow’sjazzml. Thank you Evan ! Public examples from theKeras documentation were also referenced.
Code License, Media Copyright
Code is licensed under the Apache License 2.0
Images and other media are copyrighted (Ji-Sung Kim)