data:
    n_src: 2
    sample_rate: 16000
    segment: 3
    task: sep_noisy
    train_dir: data/wav16k/min/train-360
    valid_dir: data/wav16k/min/dev
filterbank:
    kernel_size: 32
    n_filters: 512
    stride: 16
masknet:
    bn_chan: 128
    hid_chan: 512
    mask_act: relu
    n_blocks: 8
    n_repeats: 3
    n_src: 2
    skip_chan: 128
optim:
    lr: 0.001
    optimizer: adam
    weight_decay: 0.0
training:
    batch_size: 6
    early_stop: true
    epochs: 200
    half_lr: true
    num_workers: 4

Results:

On Libri2Mix min test set :

yml

si_sdr: 10.617130949793383
si_sdr_imp: 12.551811412989263
sdr: 11.231867464482065
sdr_imp: 13.059765009747343
sir: 24.461138352988346
sir_imp: 24.371856452307703
sar: 11.5649982725426
sar_imp: 4.662525705768228
stoi: 0.8701085138712695
stoi_imp: 0.2245418019822898

License notice:

This work "ConvTasNet_Libri2Mix_sepnoisy_16k" is a derivative of LibriSpeech ASR corpus by Vassil Panayotov, used underCC BY 4.0; of The WSJ0 Hipster Ambient Mixtures dataset by Whisper.ai, used under CC BY-NC 4.0 (Research only). "ConvTasNet_Libri2Mix_sepnoisy_16k" is licensed under Attribution-ShareAlike 3.0 Unported by Joris Cosentino

JorisCos/ConvTasNet_Libri2Mix_sepnoisy_16k

Asteroid model JorisCos/ConvTasNet_Libri2Mix_sepnoisy_16k

JorisCos/
ConvTasNet_Libri2Mix_sepnoisy_16k

Asteroid model `JorisCos/ConvTasNet_Libri2Mix_sepnoisy_16k`