Edit model card

Asteroid model JorisCos/ConvTasNet_Libri2Mix_sepnoisy_16k

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: 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 :

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

Downloads last month
213
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.

Space using JorisCos/ConvTasNet_Libri2Mix_sepnoisy_16k 1