readme: ---
  tags:
  - espnet
  - audio
  - audio-to-audio
  language: noinfo
  datasets:
  - clarity
  license: cc-by-4.0
  ---
  
  ## ESPnet2 ENH model 
  
  ### `popcornell/clarity21_train_enh_beamformer_mvdr`
  
  This model was trained by popcornell using clarity recipe in [espnet](https://github.com/espnet/espnet/).
  
  ### Demo: How to use in ESPnet2
  
  ```bash
  cd espnet
  
  pip install -e .
  cd egs2/clarity/enh_2021
  ./run.sh --skip_data_prep false --skip_train true --download_model popcornell/clarity21_train_enh_beamformer_mvdr
  ```
  
  <!-- Generated by ./scripts/utils/show_enh_score.sh -->
  # RESULTS
  ## Environments
  - date: `Tue Apr 12 20:54:54 UTC 2022`
  - python version: `3.9.7 (default, Sep 16 2021, 13:09:58)  [GCC 7.5.0]`
  - espnet version: `espnet 0.10.5a1`
  - pytorch version: `pytorch 1.10.1`
  - Git hash: `46eaa5eb6bea11cc33927392dca7888921491d8c`
    - Commit date: `Sat Mar 26 22:35:44 2022 +0100`
  
  
  ## ..
  
  config: conf/tuning/train_enh_beamformer_mvdr.yaml
  
  |dataset|STOI|SAR|SDR|SIR|
  |---|---|---|---|---|
  |enhanced_dev|0.96|13.02|13.02|0.00|
  
  ## 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: 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: 8
  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
  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: 1
  valid_batch_size: null
  batch_bins: 1000000
  valid_batch_bins: null
  train_shape_file:
  - exp/enh_stats_16000/train/speech_mix_shape
  - exp/enh_stats_16000/train/speech_ref1_shape
  - exp/enh_stats_16000/train/noise_ref1_shape
  valid_shape_file:
  - exp/enh_stats_16000/valid/speech_mix_shape
  - exp/enh_stats_16000/valid/speech_ref1_shape
  - exp/enh_stats_16000/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/train/wav.scp
      - speech_mix
      - sound
  -   - dump/raw/train/spk1.scp
      - speech_ref1
      - sound
  -   - dump/raw/train/noise1.scp
      - noise_ref1
      - sound
  valid_data_path_and_name_and_type:
  -   - dump/raw/dev/wav.scp
      - speech_mix
      - sound
  -   - dump/raw/dev/spk1.scp
      - speech_ref1
      - sound
  -   - dump/raw/dev/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:
      stft_consistency: false
      loss_type: mask_mse
      mask_type: null
  criterions:
  -   name: snr
      conf:
          eps: 1e-8
      wrapper: fixed_order
      wrapper_conf:
          weight: 1.0
  use_preprocessor: false
  encoder: stft
  encoder_conf:
      n_fft: 1024
      hop_length: 512
      use_builtin_complex: false
  separator: wpe_beamformer
  separator_conf:
      num_spk: 1
      loss_type: spectrum
      use_wpe: false
      use_beamformer: true
      bnet_type: blstmp
      blayers: 3
      bunits: 300
      bprojs: 320
      badim: 320
      ref_channel: 0
      use_noise_mask: true
      bnonlinear: sigmoid
      beamformer_type: mvdr_souden
      rtf_iterations: 2
      bdropout_rate: 0.0
      shared_power: true
      diagonal_loading: false
      diag_eps_wpe: 1e-4
      diag_eps_bf: 1e-4
      mask_flooring: false
      flooring_thres_wpe: 1e-6
      flooring_thres_bf: 1e-6
      use_torch_solver: true
  decoder: stft
  decoder_conf:
      n_fft: 1024
      hop_length: 512
  required:
  - output_dir
  version: 0.10.5a1
  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}: