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An open-source speech separation and enhancement library
Python
Type | Name | Latest commit message | Commit time |
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configs | Add batch_norm after rnn, refactorize training, add readme | 3 months ago | |
data | Add batch_norm after rnn, refactorize training, add readme | 3 months ago | |
losses | Add batch_norm after rnn, refactorize training, add readme | 3 months ago | |
nn | Add batch_norm after rnn, refactorize training, add readme | 3 months ago | |
LICENSE | Create LICENSE | 2 months ago | |
README.md | fixed typo | 3 months ago | |
train.py | Add batch_norm after rnn, refactorize training, add readme | 3 months ago | |
utils.py | Add batch_norm after rnn, refactorize training, add readme | 3 months ago |
README.md
ONSSEN: An Open-source Speech Separation and Enhancement Library
Supported Models
- Deep Clustering
- Chimera Net
- Chimera++
- Phase Estimation Network
- Speech Enhancement with Restoration Layers
Supported Dataset
- Wsj0-2mix (http://www.merl.com/demos/deep-clustering)
- Daps (https://archive.org/details/daps_dataset)
- Edinburgh-TTS (https://datashare.is.ed.ac.uk/handle/10283/2791)
Requirements
- PyTorch
- LibRosa
- NumPy
Usage
You can simply use the existing config JSON file or customize your config file to train the enhancement or separation model.
python train.py -c configs/dc_config.json
Citing
If you use onssen for your research project, please cite one of the following bibtex citations:
@inproceedings {onssen,
author = {Zhaoheng Ni and Michael Mandel},
title = "ONSSEN: An Open-source Speech Separation and Enhancement Library",
publisher = "under review",
year = 2019
}
@Misc{onssen,
author = {Zhaoheng Ni and Michael Mandel},
title = "ONSSEN: An Open-source Speech Separation and Enhancement Library",
howpublished = {\url{https://github.com/speechLabBcCuny/onssen}},
year = {2019}
}