CAESynth: Real-Time Timbre Intepolation and Pitch Control with Conditional Autoencoders

This is the original python implementation of the CAESynth paper, presented at the IEEE International Workshop on Machine Learning for Signal Processing MLSP 2021. Please cite our work!.

@INPROCEEDINGS{9596414,
  author={Puche, Aaron Valero and Lee, Sukhan},
  booktitle={2021 IEEE 31st International Workshop on Machine Learning for Signal Processing (MLSP)}, 
  title={Caesynth: Real-Time Timbre Interpolation and Pitch Control with Conditional Autoencoders}, 
  year={2021}, volume={}, number={}, pages={1-6},
  doi={10.1109/MLSP52302.2021.9596414}}

Dependencies

The necessary python libraries to run our experience can be directly downloaded executing the following command:

pip install -r requirements.txt

Datasets

Both NSynth and FreeSoundDataset50k can be downloaded at the provided links. The datasets should be stored in the ./data/ directory.

Training

In this implementation, we opt for summarizing the training configuration with external json files located in the ./option/ directory. Customize your own configuration file following similar structure to the already existing examples. Once the configuration file is ready, start the training with the following command.

python train.py --opt_file "./options/config_file_name.json"