This repository contains the code used to conduct the experiments for our bachelor thesis. You can read the full text here. We have an accompanying site with sound examples here.
Each of the models has its own code dependencies, so we ran each model in a different Python virtual environment.
We used Poetry for this, but any other environment management will work.
The approach is to create a virtual environment in the correct folder, install the dependencies listed in pyproject.toml
or requirements.txt
,
and then run pip install -r requirements_cuda110.txt
to install the latest PyTorch version in that virtual environment.
The folder experiments/wavegan
contains our adaptation of the WaveGAN model, based on this PyTorch version.
We compared the progressive WaveGAN versions to some other models:
These all also got their own folder in experiments/
, and we made some small changes to adapt these to our goals.
The folder notebooks/quality
contains the source code for the quality measure we defined for evaluating kick drum sample quality.
The folder notebooks/
further contains some jupyter notebooks that document some informal experiments we conducted during the design of this quality measure.
The results
folder contains some config file, samples and quality measure graphs from a couple of our experiments.