#LSTMetallica
A LSTM network that learns from the drum tracks of Metallica and generates new tracks.
Prequisite
- keras, a deeplearning framework
- python-midi, to get midi file
- numpy, probably you already have it.
Usage
- Clone the repo
$ python main_lstM_etallica.py
to get generated drum track in text file- text->midi:
$ python main_post_process.py
- this is when you need python-midi - Use this text file, an aggregated-and-encoded text file for Metallica's drum tracks, to do something more
- This folder contains the original drum midi tracks.
External links
- Details in my blog post
- Results on soundcloud and +1 more result
- Similar work on jazz chord progression: github repository, blog post, soundcloud
Citation
Text-based LSTM networks for Automatic Music Composition, Keunwoo Choi, George Fazekas, Mark Sandler, 1st Conference on Computer Simulation of Musical Creativity, Huddersfield, UK, 2016, arXiv, pdf