Asteroid model JorisCos/ConvTasNet_Libri3Mix_sepnoisy_8k
Description:
This model was trained by Joris Cosentino using the librimix recipe in Asteroid.
It was trained on the sep_noisy
task of the Libri3Mix dataset.
Training config:
data:
n_src: 3
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
n_src: 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 Libri3Mix min test set :
si_sdr: 5.978836560066222
si_sdr_imp: 10.388889689413096
sdr: 6.8651365291740225
sdr_imp: 10.928018056925016
sir: 14.997089638783114
sir_imp: 18.08248357801549
sar: 8.127504792061933
sar_imp: -0.7869320540959925
stoi: 0.7669414686111115
stoi_imp: 0.20416563213078837
License notice:
This work "ConvTasNet_Libri3Mix_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_Libri3Mix_sepnoisy_8k" is licensed under Attribution-ShareAlike 3.0 Unported by Joris Cosentino
- Downloads last month
- 46
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.