README.md

metadata

tags:
  - audio-to-audio
  - asteroid
  - audio
  - audio-source-separation
datasets:
  - wham
  - sep_clean
license: cc-by-sa-4.0

Asteroid model mpariente/DPRNNTasNet(ks=16)_WHAM!_sepclean

♻️ Imported from https://zenodo.org/record/3903795#.X8pMBRNKjUI

This model was trained by Manuel Pariente using the wham/DPRNN recipe in Asteroid. It was trained on the sep_clean task of the WHAM! dataset.

Demo: How to use in Asteroid

# coming soon

Training config

• data:
  • mode: min
  • nondefault_nsrc: None
  • sample_rate: 8000
  • segment: 2.0
  • task: sep_clean
  • train_dir: data/wav8k/min/tr
  • valid_dir: data/wav8k/min/cv
• filterbank:
  • kernel_size: 16
  • n_filters: 64
  • stride: 8
• main_args:
  • exp_dir: exp/train_dprnn_ks16/
  • help: None
• masknet:
  • bidirectional: True
  • bn_chan: 128
  • chunk_size: 100
  • dropout: 0
  • hid_size: 128
  • hop_size: 50
  • in_chan: 64
  • mask_act: sigmoid
  • n_repeats: 6
  • n_src: 2
  • out_chan: 64
• optim:
  • lr: 0.001
  • optimizer: adam
  • weight_decay: 1e-05
• positional arguments:
• training:
  • batch_size: 6
  • early_stop: True
  • epochs: 200
  • gradient_clipping: 5
  • half_lr: True
  • num_workers: 6

Results

• si_sdr: 18.227683982688003
• si_sdr_imp: 18.22883576588251
• sdr: 18.617789605060587
• sdr_imp: 18.466745426438173
• sir: 29.22773720052717
• sir_imp: 29.07669302190474
• sar: 19.116352171914485
• sar_imp: -130.06009796503054
• stoi: 0.9722025377865715
• stoi_imp: 0.23415680987800583

Citing Asteroid

@inproceedings{Pariente2020Asteroid,
    title={Asteroid: the {PyTorch}-based audio source separation toolkit for researchers},
    author={Manuel Pariente and Samuele Cornell and Joris Cosentino and Sunit Sivasankaran and
            Efthymios Tzinis and Jens Heitkaemper and Michel Olvera and Fabian-Robert Stöter and
            Mathieu Hu and Juan M. Martín-Doñas and David Ditter and Ariel Frank and Antoine Deleforge
            and Emmanuel Vincent},
    year={2020},
    booktitle={Proc. Interspeech},
}

Or on arXiv:

@misc{pariente2020asteroid,
      title={Asteroid: the PyTorch-based audio source separation toolkit for researchers}, 
      author={Manuel Pariente and Samuele Cornell and Joris Cosentino and Sunit Sivasankaran and Efthymios Tzinis and Jens Heitkaemper and Michel Olvera and Fabian-Robert Stöter and Mathieu Hu and Juan M. Martín-Doñas and David Ditter and Ariel Frank and Antoine Deleforge and Emmanuel Vincent},
      year={2020},
      eprint={2005.04132},
      archivePrefix={arXiv},
      primaryClass={eess.AS}
}