https://github.com/jisungk/deepjazz

Deep learning driven jazz generation using Keras & Theano!
https://github.com/jisungk/deepjazz

deep-learning jazz keras lstm machine-learning music neural-networks rnn theano

Last synced: 23 days ago
JSON representation

Deep learning driven jazz generation using Keras & Theano!

• Host: GitHub
• URL: https://github.com/jisungk/deepjazz
• Owner: jisungk
• License: apache-2.0
• Created: 2016-04-02T01:00:05.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2019-05-29T22:32:44.000Z (over 5 years ago)
• Last Synced: 2024-09-30T16:41:39.438Z (about 1 month ago)
• Topics: deep-learning, jazz, keras, lstm, machine-learning, music, neural-networks, rnn, theano
• Language: Python
• Homepage: http://deepjazz.io
• Size: 11.7 MB
• Stars: 2,874
• Watchers: 110
• Forks: 442
• Open Issues: 12
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome - jisungk/deepjazz - Deep learning driven jazz generation using Keras & Theano! (Python)
• awesome-keras - deepjazz - Deep learning-driven jazz music generation using Keras and Theano. (Examples/Notebooks)

README

        
Note: deepjazz is no longer being actively developed. It may be refactored at some point in the future. Goodbye and thank you for your interest 😢

***

![deepjazz](https://cloud.githubusercontent.com/assets/9053987/16575656/901989da-424f-11e6-9f54-6a04199e69f5.png)

### Using Keras & Theano for deep learning driven jazz generation

I built [*deepjazz*](https://deepjazz.io) in 36 hours at a hackathon. It uses Keras & Theano, two deep learning libraries, to generate jazz music. Specifically, it builds a two-layer [LSTM](http://deeplearning.net/tutorial/lstm.html), learning from the given MIDI file. It uses deep learning, the AI tech that powers [Google's AlphaGo](https://deepmind.com/alpha-go.html) and [IBM's Watson](https://www.ibm.com/smarterplanet/us/en/ibmwatson/what-is-watson.html), **to make music -- something that's considered as deeply human**.

[![SoundCloud](https://jisungk.github.io/deepjazz/img/button_soundcloud.png)](https://soundcloud.com/deepjazz-ai)  

Check out deepjazz's music on **[SoundCloud](https://soundcloud.com/deepjazz-ai)**!

### Dependencies

* [Keras](http://keras.io/#installation)

* [Theano](http://deeplearning.net/software/theano/install.html#bleeding-edge-install-instructions) ("bleeding-edge" version on GitHub)

* [music21](http://web.mit.edu/music21/doc/installing/index.html)

### Instructions

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]

```

Note: running Keras/Theano on GPU is formally supported for only NVIDIA cards (CUDA backend).

Note: `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.

### Author

[Ji-Sung Kim](https://jisungkim.com)  

Princeton University, Department of Computer Science  

hello (at) jisungkim.com  

### Citations

This project develops a lot of preprocessing code (with permission) from Evan Chow's [jazzml](https://github.com/evancchow/jazzml). Thank you [Evan](https://www.linkedin.com/in/evancchow)! Public examples from the [Keras documentation](https://github.com/fchollet/keras) 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)