Asteroid model JorisCos/ConvTasNet_Libri2Mix_sepnoisy_8k

Imported from Zenodo

Description:

This model was trained by Joris Cosentino using the librimix recipe in Asteroid. It was trained on the sep_noisy task of the Libri2Mix dataset.

Training config:

data:
    n_src: 2
    sample_rate: 8000
    segment: 3
    task: sep_noisy
    train_dir: data/wav8k/min/train-360
    valid_dir: data/wav8k/min/dev
filterbank:
    kernel_size: 16
    n_filters: 512
    stride: 8
masknet:
    bn_chan: 128
    hid_chan: 512
    mask_act: relu
    n_blocks: 8
    n_repeats: 3
    skip_chan: 128
optim:
    lr: 0.001
    optimizer: adam
    weight_decay: 0.0
training:
    batch_size: 24
    early_stop: True
    epochs: 200
    half_lr: True
    num_workers: 4

Results:

On Libri2Mix min test set :

si_sdr: 9.944424856077259
si_sdr_imp: 11.939395359731192
sdr: 10.701526190782072
sdr_imp: 12.481757547845662
sir: 22.633644975545575
sir_imp: 22.45666740833025
sar: 11.131644100944868
sar_imp: 4.248489589311784
stoi: 0.852048619949357
stoi_imp: 0.2071994899565506

License notice:

This work "ConvTasNet_Libri2Mix_sepnoisy_8k" is a derivative of LibriSpeech ASR corpus by Vassil Panayotov, used under CC 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_8k" is licensed under AAttribution-ShareAlike 3.0 Unported by Joris Cosentino

Downloads last month
162
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.