• Fusion GAN is an extension of vanillia GAN, it can be used to fuse patterns from different domains.
• Current implementation is based on discretized sequence modeling, so can be directly applied for any problem of such kind, such as word sequence.
• Replacing the generator as you want, you can fuse any type of data. e.g., use CNN as generator, it's possible to fuse two different styles, say a fusion of Van Gogh and Picasso.

Codes for the paper

Zhiqian Chen, Chih-Wei Wu, Cheng-Yen Lu, Alexander Lerch, Chang-Tien Lu, Learning to Fuse Music Genres with Generative Adversarial Dual Learning, International Conference on Data Mining(ICDM), New Orleans, USA, 2017

Please refer to https://imczq.com/publication/17_fusiongan_icdm/

required python package

numpy tensorflow magenta.music pandas midi music21 

Files description

• discriminator.py: GAN discriminator class
• generator.py: GAN generator class
• dataloader.py: data handler
• midi_io.py: music data process, such as MIDI to seq and seq to MIDI
• rollout.py: rollout for delayed update in reinforcement learning

Download all files and run

python fusion_gan.py

*.pkl is pre-processed files of music, but they cannot be recovered into original music

Please see midi_io.py in which there are functions for converting between MIDI and number sequences. Then, update the data path at main function of fusion_gan.py

@article{fusiongan-icdm
  author    = {Zhiqian Chen and
               Chih{-}Wei Wu and
               Yen{-}Cheng Lu and
               Alexander Lerch and
               Chang{-}Tien Lu},
  title     = {Learning to Fuse Music Genres with Generative Adversarial Dual Learning},
  booktitle = {Proceedings of the The IEEE International Conference on Data Mining},
  year      = {2017},
}