readme: ---
  tags:
  - espnet
  - audio
  - audio-to-audio
  language: 
  datasets:
  - chime4
  license: cc-by-4.0
  ---
  
  ## ESPnet2 ENH model 
  
  ### `espnet/Wangyou_Zhang_chime4_enh_train_enh_beamformer_mvdr_raw`
  
  This model was trained by Wangyou Zhang using chime4 recipe in [espnet](https://github.com/espnet/espnet/).
  
  ### Demo: How to use in ESPnet2
  
  ```bash
  cd espnet
  
  pip install -e .
  cd egs2/chime4/enh1
  ./run.sh --skip_data_prep false --skip_train true --download_model espnet/Wangyou_Zhang_chime4_enh_train_enh_beamformer_mvdr_raw
  ```
  
  
  
  ## ENH config
  
  <details><summary>expand</summary>
  
  ```
  config: conf/tuning/train_enh_beamformer_mvdr.yaml
  print_config: false
  log_level: INFO
  dry_run: false
  iterator_type: sequence
  output_dir: exp/enh_train_enh_beamformer_mvdr_raw
  ngpu: 1
  seed: 0
  num_workers: 4
  num_att_plot: 3
  dist_backend: nccl
  dist_init_method: env://
  dist_world_size: 2
  dist_rank: 0
  local_rank: 0
  dist_master_addr: localhost
  dist_master_port: 35841
  dist_launcher: null
  multiprocessing_distributed: true
  cudnn_enabled: true
  cudnn_benchmark: false
  cudnn_deterministic: true
  collect_stats: false
  write_collected_feats: false
  max_epoch: 70
  patience: 4
  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
  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
  unused_parameters: false
  use_tensorboard: true
  use_wandb: false
  wandb_project: null
  wandb_id: null
  pretrain_path: null
  init_param: []
  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_16k/train/speech_mix_shape
  - exp/enh_stats_16k/train/speech_ref1_shape
  - exp/enh_stats_16k/train/noise_ref1_shape
  valid_shape_file:
  - exp/enh_stats_16k/valid/speech_mix_shape
  - exp/enh_stats_16k/valid/speech_ref1_shape
  - exp/enh_stats_16k/valid/noise_ref1_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: 500
  chunk_shift_ratio: 0.5
  num_cache_chunks: 1024
  train_data_path_and_name_and_type:
  -   - dump/raw/tr05_simu_isolated_6ch_track/wav.scp
      - speech_mix
      - sound
  -   - dump/raw/tr05_simu_isolated_6ch_track/spk1.scp
      - speech_ref1
      - sound
  -   - dump/raw/tr05_simu_isolated_6ch_track/noise1.scp
      - noise_ref1
      - sound
  valid_data_path_and_name_and_type:
  -   - dump/raw/dt05_simu_isolated_6ch_track/wav.scp
      - speech_mix
      - sound
  -   - dump/raw/dt05_simu_isolated_6ch_track/spk1.scp
      - speech_ref1
      - sound
  -   - dump/raw/dt05_simu_isolated_6ch_track/noise1.scp
      - noise_ref1
      - 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: 0.5
      patience: 1
  init: xavier_uniform
  model_conf:
      loss_type: mask_mse
      mask_type: PSM^2
  use_preprocessor: false
  encoder: stft
  encoder_conf:
      n_fft: 512
      hop_length: 128
  separator: wpe_beamformer
  separator_conf:
      num_spk: 1
      loss_type: mask_mse
      use_wpe: false
      wnet_type: blstmp
      wlayers: 3
      wunits: 300
      wprojs: 320
      wdropout_rate: 0.0
      taps: 5
      delay: 3
      use_dnn_mask_for_wpe: true
      use_beamformer: true
      bnet_type: blstmp
      blayers: 3
      bunits: 512
      bprojs: 512
      badim: 320
      ref_channel: 3
      use_noise_mask: true
      beamformer_type: mvdr_souden
      bdropout_rate: 0.0
  decoder: stft
  decoder_conf:
      n_fft: 512
      hop_length: 128
  required:
  - output_dir
  version: 0.9.7
  distributed: true
  ```
  
  </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{li2021espnetse,
    title={{ESPnet-SE}: End-to-End Speech Enhancement and Separation Toolkit Designed for {ASR} Integration},
    author={Li, Chenda and Shi, Jing and Zhang, Wangyou and Subramanian, Aswin Shanmugam and Chang, Xuankai and Kamo, Naoyuki and Hira, Moto and Hayashi, Tomoki and Boeddeker, Christoph and Chen, Zhuo and Watanabe, Shinji},
    booktitle={Proc. IEEE Spoken Language Technology Workshop (SLT)},
    pages={785--792},
    year={2021},
  }
  
  ```
  
  or arXiv:
  
  ```bibtex
  @misc{watanabe2018espnet,
    title={ESPnet: End-to-End Speech Processing Toolkit}, 
    author={Shinji Watanabe and Takaak