Releases: merlresearch/cocktail-fork-separation
Releases · merlresearch/cocktail-fork-separation
Cocktail Fork Separation 1.2.0 Release Notes
Improvement by @gwichern:
- Add loudness and equalization normalized pre-trained models
Full Changelog: v1.1.0...v1.2.0
Cocktail Fork Separation 1.1.0 Release Notes
Improvements and bugfixes by @gwichern:
- Error checking in the dataset to ensure people are using the right version of the DivideAndRemaster dataset
- Add the ability to train using a simplified loss function without scale invariance
- Add the ability to add residual back to estimated sources during training and test, as this was shown to be valuable for the challenge dataset
- Make the default pre-trained model be a new model that was trained with the simplified scale-dependent loss function. Rename the original pre-trained model as "paper_mrx_pre_trained_weights.pth," but continue to include it since this exactly reproduces the results from our paper
- Add pyloudnorm as a dependency and use it normalize input when separating files to be more robust to input signal level
Full Changelog: v1.0.0...v1.1.0
Cocktail Fork Separation 1.0.0 Release Notes
Initial release created by @gwichern