Repository for Semi-Supervised Synthesizer Sound Matching with Differentiable DSP

Accompanying website:

Files

• gen_dataset.py
  • Used for dataset generation
• train.py
  • Training script
• test.py
  • Testing script
• configs
  • hydra configs for experiments

Usage

Dataset generation

Specify the synth architecture from configs/synth (in this case, h2of_fx_env which is the FX-Env setting from the paper).

python gen_dataset.py [generated in-domain dataset dir] configs/synth/h2of_fx_env.yaml

Training

Edit configs/experiments/exp with dataset directory (id_base, data_cfgs.ood.base_dir).

Train a model with the Synth setting:

python train.py experiment=exp synth=h2of_fx_env

Change the loss function to parameter loss only (P-loss setting):

python train.py experiment=exp synth=h2of_fx_env loss=only_param

Resume with the Real setting:

python train.py experiment=exp synth=h2of_fx_env data.train_key=ood ckpt=[checkpoint file at 200th epoch of Synth]

Resume with the Even setting:

python train.py experiment=exp synth=h2of_fx_env data.train_key=id loss=even_spec_fro ckpt=[checkpoint file at 50th epoch of P-loss] trainer.max_epochs=200

python train.py experiment=exp synth=h2of_fx_env data.train_key=[id,ood] loss=even_spec_fro ckpt=[checkpoint file of the above run]