README.md

---
tags:
- espnet
- audio
- audio-to-audio
language: en
datasets:
- wsj0_2mix
license: cc-by-4.0
---

## ESPnet2 ENH model 

### `Zhaoheng/svoice_wsj0_2mix`

This model was trained by Zhaoheng Ni using wsj0_2mix recipe in [espnet](https://github.com/espnet/espnet/).

### Demo: How to use in ESPnet2

```bash
cd espnet
git checkout 5ae7c9580f85dae5bc81cb1e845366c251d871ac
pip install -e .
cd egs2/wsj0_2mix/enh1
./run.sh --skip_data_prep false --skip_train true --download_model Zhaoheng/svoice_wsj0_2mix
```

<!-- Generated by ./scripts/utils/show_enh_score.sh -->
# RESULTS
## Environments
- date: `Thu Apr 14 09:47:05 UTC 2022`
- python version: `3.8.12 (default, Oct 12 2021, 13:49:34)  [GCC 7.5.0]`
- espnet version: `espnet 0.10.7a1`
- pytorch version: `pytorch 1.10.1+cu111`
- Git hash: `9dbe4179b866b994f6914ef52ea7483696d22760`
  - Commit date: `Wed Mar 16 13:25:26 2022 +0000`


## ..

config: conf/tuning/train_enh_svoice.yaml

|dataset|STOI|SAR|SDR|SIR|SI_SNR|
|---|---|---|---|---|---|
|enhanced_cv_min_8k|0.97|21.44|20.98|32.21|20.67|
|enhanced_tt_min_8k|0.98|21.41|20.96|32.27|20.66|

## ENH config

<details><summary>expand</summary>

```
config: conf/tuning/train_enh_svoice.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: chunk
output_dir: exp/enh_train_enh_svoice_raw
ngpu: 4
seed: 0
num_workers: 4
num_att_plot: 3
dist_backend: nccl
dist_init_method: env://
dist_world_size: null
dist_rank: null
local_rank: 0
dist_master_addr: null
dist_master_port: null
dist_launcher: null
multiprocessing_distributed: false
unused_parameters: false
sharded_ddp: false
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
collect_stats: false
write_collected_feats: false
max_epoch: 150
patience: 20
val_scheduler_criterion:
- valid
- loss
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
-   - valid
    - si_snr
    - max
-   - valid
    - loss
    - min
keep_nbest_models: 1
nbest_averaging_interval: 0
grad_clip: 5.0
grad_clip_type: 2.0
grad_noise: false
accum_grad: 1
no_forward_run: false
resume: true
train_dtype: float32
use_amp: false
log_interval: null
use_matplotlib: true
use_tensorboard: true
use_wandb: false
wandb_project: null
wandb_id: null
wandb_entity: null
wandb_name: null
wandb_model_log_interval: -1
detect_anomaly: false
pretrain_path: null
init_param: []
ignore_init_mismatch: false
freeze_param: []
num_iters_per_epoch: null
batch_size: 8
valid_batch_size: null
batch_bins: 1000000
valid_batch_bins: null
train_shape_file:
- exp/enh_stats_8k/train/speech_mix_shape
- exp/enh_stats_8k/train/speech_ref1_shape
- exp/enh_stats_8k/train/speech_ref2_shape
valid_shape_file:
- exp/enh_stats_8k/valid/speech_mix_shape
- exp/enh_stats_8k/valid/speech_ref1_shape
- exp/enh_stats_8k/valid/speech_ref2_shape
batch_type: folded
valid_batch_type: null
fold_length:
- 80000
- 80000
- 80000
sort_in_batch: descending
sort_batch: descending
multiple_iterator: false
chunk_length: 16000
chunk_shift_ratio: 0.5
num_cache_chunks: 1024
train_data_path_and_name_and_type:
-   - dump/raw/tr_min_8k/wav.scp
    - speech_mix
    - sound
-   - dump/raw/tr_min_8k/spk1.scp
    - speech_ref1
    - sound
-   - dump/raw/tr_min_8k/spk2.scp
    - speech_ref2
    - sound
valid_data_path_and_name_and_type:
-   - dump/raw/cv_min_8k/wav.scp
    - speech_mix
    - sound
-   - dump/raw/cv_min_8k/spk1.scp
    - speech_ref1
    - sound
-   - dump/raw/cv_min_8k/spk2.scp
    - speech_ref2
    - sound
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
valid_max_cache_size: null
optim: adam
optim_conf:
    lr: 0.001
    eps: 1.0e-08
    weight_decay: 0
scheduler: reducelronplateau
scheduler_conf:
    mode: min
    factor: 0.7
    patience: 1
init: xavier_uniform
model_conf:
    stft_consistency: false
    loss_type: mask_mse
    mask_type: null
criterions:
-   name: si_snr
    conf:
        eps: 1.0e-07
    wrapper: multilayer_pit
    wrapper_conf:
        weight: 1.0
        independent_perm: true
use_preprocessor: false
encoder: same
encoder_conf: {}
separator: svoice
separator_conf:
    enc_dim: 128
    kernel_size: 8
    hidden_size: 128
    num_spk: 2
    num_layers: 6
    segment_size: 128
    input_normalize: false
decoder: same
decoder_conf: {}
required:
- output_dir
version: 0.10.7a1
distributed: false
```

</details>



### Citing ESPnet

```BibTex
@inproceedings{watanabe2018espnet,
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  title={{ESPnet}: End-to-End Speech Processing Toolkit},
  year={2018},
  booktitle={Proceedings of Interspeech},
  pages={2207--2211},
  doi={10.21437/Interspeech.2018-1456},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}


@inproceedings{ESPnet-SE,
  author = {Chenda Li and Jing Shi and Wangyou Zhang and Aswin Shanmugam Subramanian and Xuankai Chang and 
  Naoyuki Kamo and Moto Hira and Tomoki Hayashi and Christoph B{"o}}ddeker and Zhuo Chen and Shinji Watanabe}


@inproceedings{nachmani2020voice,
  title={Voice separation with an unknown number of multiple speakers},
  author={Nachmani, Eliya and Adi, Yossi and Wolf, Lior},
  booktitle={International Conference on Machine Learning},
  pages={7164--7175},
  year={2020},
  organization={PMLR}
}


```

or arXiv:

```bibtex
@misc{watanabe2018espnet,
  title={ESPnet: End-to-End Speech Processing Toolkit}, 
  author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
  year={2018},
  eprint={1804.00015},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}
```