readme: ---
  tags:
  - espnet
  - audio
  - automatic-speech-recognition
  language: en
  datasets:
  - chime4
  license: cc-by-4.0
  ---
  
  ## ESPnet2 ASR model 
  
  ### `pyf98/chime4_e_branchformer_e10`
  
  This model was trained by Yifan Peng using chime4 recipe in [espnet](https://github.com/espnet/espnet/).
  
  References:
  - [E-Branchformer: Branchformer with Enhanced merging for speech recognition (SLT 2022)](https://arxiv.org/abs/2210.00077)
  - [Branchformer: Parallel MLP-Attention Architectures to Capture Local and Global Context for Speech Recognition and Understanding (ICML 2022)](https://proceedings.mlr.press/v162/peng22a.html)
  
  ### Demo: How to use in ESPnet2
  
  Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html)
  if you haven't done that already.
  
  ```bash
  cd espnet
  git checkout ad91279f0108d54bd22abe29671b376f048822c5
  pip install -e .
  cd egs2/chime4/asr1
  ./run.sh --skip_data_prep false --skip_train true --download_model pyf98/chime4_e_branchformer_e10
  ```
  
  <!-- Generated by scripts/utils/show_asr_result.sh -->
  # RESULTS
  ## Environments
  - date: `Wed Dec 28 15:49:24 EST 2022`
  - python version: `3.9.15 (main, Nov 24 2022, 14:31:59)  [GCC 11.2.0]`
  - espnet version: `espnet 202211`
  - pytorch version: `pytorch 1.12.1`
  - Git hash: `f9a8009aef6ff9ba192a78c19b619ae4a9f3b9d2`
    - Commit date: `Wed Dec 28 00:30:54 2022 -0500`
  
  ## asr_train_asr_e_branchformer_e10_mlp1024_linear1024_macaron_lr1e-3_warmup25k_raw_en_char_sp
  ### WER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/dt05_real_beamformit_5mics|1640|27119|93.7|5.0|1.2|0.6|6.8|52.5|
  |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/dt05_simu_beamformit_5mics|1640|27120|92.4|6.1|1.6|0.7|8.4|58.2|
  |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/et05_real_beamformit_5mics|1320|21409|90.2|8.0|1.8|1.0|10.8|60.2|
  |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/et05_simu_beamformit_5mics|1320|21416|88.4|9.3|2.4|1.4|13.0|66.1|
  
  ### CER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/dt05_real_beamformit_5mics|1640|160390|97.4|1.3|1.3|0.7|3.3|52.5|
  |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/dt05_simu_beamformit_5mics|1640|160400|96.6|1.8|1.7|0.9|4.3|58.2|
  |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/et05_real_beamformit_5mics|1320|126796|95.7|2.3|2.0|1.1|5.4|60.2|
  |decode_asr_lm_lm_train_lm_transformer_en_char_valid.loss.ave_asr_model_valid.acc.ave/et05_simu_beamformit_5mics|1320|126812|94.4|2.8|2.8|1.5|7.2|66.1|
  
  ### TER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  
  ## ASR config
  
  <details><summary>expand</summary>
  
  ```
  config: conf/tuning/train_asr_e_branchformer_e10_mlp1024_linear1024_macaron_lr1e-3_warmup25k.yaml
  print_config: false
  log_level: INFO
  dry_run: false
  iterator_type: sequence
  output_dir: exp/asr_train_asr_e_branchformer_e10_mlp1024_linear1024_macaron_lr1e-3_warmup25k_raw_en_char_sp
  ngpu: 1
  seed: 2022
  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: 33561
  dist_launcher: null
  multiprocessing_distributed: true
  unused_parameters: false
  sharded_ddp: false
  cudnn_enabled: true
  cudnn_benchmark: false
  cudnn_deterministic: true
  collect_stats: false
  write_collected_feats: false
  max_epoch: 50
  patience: null
  val_scheduler_criterion:
  - valid
  - loss
  early_stopping_criterion:
  - valid
  - loss
  - min
  best_model_criterion:
  -   - valid
      - acc
      - max
  keep_nbest_models: 10
  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: true
  log_interval: null
  use_matplotlib: true
  use_tensorboard: true
  create_graph_in_tensorboard: false
  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: 20
  valid_batch_size: null
  batch_bins: 15000000
  valid_batch_bins: null
  train_shape_file:
  - exp/asr_stats_raw_en_char_sp/train/speech_shape
  - exp/asr_stats_raw_en_char_sp/train/text_shape.char
  valid_shape_file:
  - exp/asr_stats_raw_en_char_sp/valid/speech_shape
  - exp/asr_stats_raw_en_char_sp/valid/text_shape.char
  batch_type: numel
  valid_batch_type: null
  fold_length:
  - 80000
  - 150
  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_multi_noisy_si284_sp/wav.sc