zhaoforever / onssen

An open-source speech separation and enhancement library

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}
}