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  1. README.md +41 -41
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@@ -10,8 +10,8 @@ license: cc-by-sa-3.0
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  inference: false
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  ---
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- ## Asteroid model `mpariente/ConvTasNet_Libri3Mix_sep_noisy`
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- Imported from [Zenodo](https://zenodo.org/record/4020529)
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  ## Description:
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  This model was trained by Takhir Mirzaev using the Librimix/ConvTasNet recipe in Asteroid.
@@ -20,50 +20,50 @@ It was trained on the `sep_noisy` task of the Libri3Mix dataset.
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  ## Training config:
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  ```yaml
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- data:
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- n_src: 3
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- sample_rate: 8000
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- segment: 3
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- task: sep_noisy
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- train_dir: data/wav8k/min/train-360
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- valid_dir: data/wav8k/min/dev
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- filterbank:
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- kernel_size: 16
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- n_filters: 512
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- stride: 8
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- masknet:
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- bn_chan: 128
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- hid_chan: 512
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- mask_act: relu
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- n_blocks: 8
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- n_repeats: 3
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- skip_chan: 128
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- optim:
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- lr: 0.001
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- optimizer: adam
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- weight_decay: 0.0
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- positional arguments:
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- training:
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- batch_size: 4
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- early_stop: True
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- epochs: 200
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- half_lr: True
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- num_workers: 4
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  ```
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  ## Results:
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  ```yaml
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- si_sdr: 6.824750632456865
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- si_sdr_imp: 11.234803761803752
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- sdr: 7.715799858488098
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- sdr_imp: 11.778681386239114
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- sir: 16.442141130818637
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- sir_imp: 19.527535070051055
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- sar: 8.757864265661263
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- sar_imp: -0.15657258049670303
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- stoi: 0.7854554136619554
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- stoi_imp: 0.22267957718163015
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  ```
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  inference: false
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  ---
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+ ## Asteroid model
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+ Imported from this Zenodo [model page](https://zenodo.org/record/4020529).
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  ## Description:
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  This model was trained by Takhir Mirzaev using the Librimix/ConvTasNet recipe in Asteroid.
 
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  ## Training config:
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  ```yaml
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+ data:
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+ n_src: 3
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+ sample_rate: 8000
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+ segment: 3
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+ task: sep_noisy
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+ train_dir: data/wav8k/min/train-360
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+ valid_dir: data/wav8k/min/dev
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+ filterbank:
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+ kernel_size: 16
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+ n_filters: 512
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+ stride: 8
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+ masknet:
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+ bn_chan: 128
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+ hid_chan: 512
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+ mask_act: relu
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+ n_blocks: 8
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+ n_repeats: 3
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+ skip_chan: 128
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+ optim:
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+ lr: 0.001
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+ optimizer: adam
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+ weight_decay: 0.0
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+ positional arguments:
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+ training:
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+ batch_size: 4
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+ early_stop: True
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+ epochs: 200
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+ half_lr: True
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+ num_workers: 4
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  ```
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  ## Results:
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  ```yaml
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+ si_sdr: 6.824750632456865
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+ si_sdr_imp: 11.234803761803752
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+ sdr: 7.715799858488098
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+ sdr_imp: 11.778681386239114
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+ sir: 16.442141130818637
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+ sir_imp: 19.527535070051055
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+ sar: 8.757864265661263
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+ sar_imp: -0.15657258049670303
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+ stoi: 0.7854554136619554
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+ stoi_imp: 0.22267957718163015
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  ```
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