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}
}
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