https://github.com/samim23/Novelty-Search-Live

Musical Novelty Search: Evolutionary Algorithms + Ableton Live
https://github.com/samim23/Novelty-Search-Live

ableton-live evolutionary-algorithms novelty-search

Last synced: 3 months ago
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Musical Novelty Search: Evolutionary Algorithms + Ableton Live

• Host: GitHub
• URL: https://github.com/samim23/Novelty-Search-Live
• Owner: samim23
• License: gpl-3.0
• Created: 2017-05-28T23:40:37.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2017-05-29T13:57:56.000Z (about 7 years ago)
• Last Synced: 2023-10-20T22:57:39.355Z (9 months ago)
• Topics: ableton-live, evolutionary-algorithms, novelty-search
• Language: Python
• Homepage:
• Size: 19.5 KB
• Stars: 96
• Watchers: 11
• Forks: 18
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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• my-awesome-stars - samim23/Novelty-Search-Live - Musical Novelty Search: Evolutionary Algorithms + Ableton Live (Python)

README

        
# Novelty Search Live

Novelty Search Live is a experimental open-source tool that helps musicians find musical inspiration in Ableton Live. It uses a evolutionary algorithm to continuously evolve new audio-clip and synth-parameter combinations, guided exclusively by Novelty Search. Finally, it takes the countless new musical ideas it has discovered, and generates a map with t-SNE which is interactively browsable. Read more: https://medium.com/@samim/musical-novelty-search-2177c2a249cc

## Usage

After everything is setup and Ableton Live is open, run **python noveltysearchlive.py** from your console to start.

You can tweak the following parameters via the command line:        

--name (Song Name)           

--waittime        

--iterationtime        

--populationsize       

--crossoverrate       

--mutationrate       

--tournamentsize        

And tweak many more settings inside the "noveltysearchlive.py" config section.

## Requirements

- ableton: https://www.ableton.com/

- python: https://www.python.org/

- pylive: https://github.com/ideoforms/pylive

- argparse: https://docs.python.org/3/library/argparse.html

- numpy: https://www.scipy.org/scipylib/download.html

- deap: https://github.com/DEAP/deap

- sklearn: http://scikit-learn.org/stable/install.html

- matplotlib: https://matplotlib.org/faq/installing_faq.html

- annoy: https://github.com/spotify/annoy