| --- |
| tags: |
| - asteroid |
| - audio |
| - VADNet |
| - VAD |
| - Voice Activity Detection |
| datasets: |
| - LibriVAD |
| license: cc-by-sa-4.0 |
| --- |
| |
| ## Asteroid model `JorisCos/VAD_Net` |
| |
| Description: |
| |
| This model was trained by Joris Cosentino using the librimix recipe in [Asteroid](https://github.com/asteroid-team/asteroid). |
| It was trained on the `enh_single` task of the Libri1Mix dataset. |
|
|
| Training config: |
|
|
| ```yml |
| data: |
| segment: 3 |
| train_dir: /home/jcosentino/VAD_dataset/metadata/sets/train.json |
| valid_dir: /home/jcosentino/VAD_dataset/metadata/sets/dev.json |
| filterbank: |
| kernel_size: 16 |
| n_filters: 512 |
| stride: 8 |
| main_args: |
| exp_dir: exp/full_not_causal_f1/ |
| help: null |
| masknet: |
| bn_chan: 128 |
| causal: false |
| hid_chan: 512 |
| mask_act: relu |
| n_blocks: 3 |
| n_repeats: 5 |
| skip_chan: 128 |
| optim: |
| lr: 0.001 |
| optimizer: adam |
| weight_decay: 0.0 |
| positional arguments: {} |
| training: |
| batch_size: 8 |
| early_stop: true |
| epochs: 200 |
| half_lr: true |
| num_workers: 4 |
| ``` |
| |
|
|
| Results: |
|
|
| On LibriVAD min test set : |
| ```yml |
| accuracy: 0.8196149023502931, |
| precision: 0.8305009048356607, |
| recall: 0.8869202491310206, |
| f1_score: 0.8426184545700124 |
| ``` |
|
|
|
|
| License notice: |
|
|
| This work "VAD_Net" is a derivative of [LibriSpeech ASR corpus](http://www.openslr.org/12) by Vassil Panayotov, |
| used under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/); of The [DNS challenge](https://github.com/microsoft/DNS-Challenge) noises, [Attribution-ShareAlike 3.0 Unported](https://creativecommons.org/licenses/by-sa/3.0/). |
| "VAD_Net" is licensed under [Attribution-ShareAlike 3.0 Unported](https://creativecommons.org/licenses/by-sa/3.0/) by Joris Cosentino |
