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https://github.com/google-research/sound-separation


https://github.com/google-research/sound-separation

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README

        

# Sound Separation

Open-source datasets and deep learning models for separating sounds.

## Datasets

* [Free Universal Sound Separation (FUSS)](https://github.com/google-research/sound-separation/blob/master/datasets/fuss/FUSS_license_doc/README.md).

* [Audio from YFCC100M videos for mixture-invariant training (MixIT)](https://github.com/google-research/sound-separation/blob/master/datasets/yfcc100m/README.md).

* [Audio-visual YFCC100M with annotations for on-screen sound separation with AudioScope](https://github.com/google-research/sound-separation/blob/master/datasets/audioscope/README.md).

* [Audio-visual YFCC100M with annotations for on-screen sound separation with AudioScopeV2](https://github.com/google-research/sound-separation/blob/master/datasets/audioscope-v2/README.md).

* [Synthetic AMI for speech separation in meeting room scenarios](https://github.com/google-research/sound-separation/blob/master/datasets/synthetic_ami/README.md).

## Models

* [Free Universal Sound Separation (FUSS) baseline separation model](https://github.com/google-research/sound-separation/tree/master/models/dcase2020_fuss_baseline/README.md).

* [Universal unsupervised separation models using mixture invariant training (MixIT)](https://github.com/google-research/sound-separation/tree/master/models/neurips2020_mixit/README.md).

* [Unsupervised separation models for birds using mixture invariant training (MixIT)](https://github.com/google-research/sound-separation/tree/master/models/bird_mixit/README.md).