Style-based Drum Synthesis with GAN Inversion Demo

TensorFlow implementation of a style-based version of the adversarial drum synth (ADS) from the paper Adversarial Synthesis of Drum Sounds @ The 2020 DAFx Conference.

Overview of proposed style-based drum synthesis system

Audio examples​

Music created using generated drum sounds​

Transforming input audio​

This drum sound does not exist​

Check out some randomly generated drum sound waveforms here

Code​

Dependencies​

Python​

Code has been developed with Python 3.6.13. It should work with other versions of Python 3, but has not been tested. Moreover, we rely on several third-party libraries, listed in requirements.txt. They can be installed with

$ pip install -r requirements.txt

Checkpoints​

The tensorflow checkpoints for loading pre-trained network weights can be download here. Unzip the folder and save it into this projects directory: "style-drumsynth/checkpoints".

Usage​

The code is contained within the drumsynth_demo.py script, which enables conditional synthesises of drum sounds using a pretrained generator.

The following control parameters are available:

• Condition: which type of drum to generate (kick, snare or hat)
• Direction: "timbral features", which principal direction to move in [0:4]
• Direction slider: How far to move in a particular direction
• Number of generations: How many drums to generate
• Stocastic Variation: Amount of inconsequential noise to inject into the generator
• Randomize: Generate by randomly sampling the latent space, or generate from a fixed, pre-computed latent vectors for a kick, snare and hat
• Encode: regenerate drum sounds stored in the style-drumsynth/input_audio

Generations are saved in the style-drumsynth/generations folder. To experiment encoding your own drums sounds, save your audio files in the "style-drumsynth/input_audio" directory.

drumsynth_demo.py arguments​

  -c CONDITION,           --condition CONDITION
                            0: kick, 1: snare, 2:hat
  -d DIRECTION,           --direction DIRECTION
                            synthesis controls [0:4]
  -ds DIRECTION_SLIDER,   --direction_slider DIRECTION_SLIDER
                            how much to move in a particular direction
  -n NUM_GENERATIONS,     --num_generations NUM_GENERATIONS
                            number of examples to generate
  -v STOCASTIC_VARIATION, --stocastic_variation STOCASTIC_VARIATION
                            amount of inconsequential noise injected
  -r RANDOMIZE,           --randomize RANDOMIZE
                            if set to False, a fixed latent vector is used to generate a drum sound from each condition
  -e ENCODE,              --encode ENCODE
                            regenerates drum sounds from encoder folder

Supporting webpage​

For more information, please visit the corresponding supporting website.

It contains the following:

• Audio examples
• Training data
• Generations
• Example usage within loop-based electronic music compositions
• Generating Drum Loops
• Interpolation demonstration
• Supplementary figures
• A link to the DAFx 2020 paper and presentation

References​

@inproceedings{drysdale2020ads,
  title={Adversarial synthesis of drum sounds},
  author={Drysdale, Jake and Tomczak, Maciek and Hockman, Jason},
  booktitle = {Proceedings of the International Conference on Digital Audio Effects (DAFx)},
  year={2020}
}

Help​

Any questions please feel free to contact me on jake.drysdale@bcu.ac.uk