| | --- |
| | 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 |
