readme: ---
  tags:
  - espnet
  - audio
  - automatic-speech-recognition
  language: en
  datasets:
  - tedlium2
  license: cc-by-4.0
  ---
  
  ## ESPnet2 ASR model 
  
  ### `pyf98/tedlium2_ctc_e_branchformer`
  
  This model was trained by Yifan Peng using tedlium2 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 e62de171f1d11015cb856f83780c61bd5ca7fa8f
  pip install -e .
  cd egs2/tedlium2/asr1
  ./run.sh --skip_data_prep false --skip_train true --download_model pyf98/tedlium2_ctc_e_branchformer
  ```
  
  <!-- Generated by scripts/utils/show_asr_result.sh -->
  # RESULTS
  ## Environments
  - date: `Fri Dec 30 20:15:46 CST 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: `e62de171f1d11015cb856f83780c61bd5ca7fa8f`
    - Commit date: `Thu Dec 29 14:18:44 2022 -0500`
  
  ## asr_train_asr_ctc_e_branchformer_e12_mlp1024_linear1024_raw_en_bpe500_sp
  ### WER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_ctc_asr_model_valid.cer_ctc.ave/dev|466|14671|92.5|5.5|2.0|1.2|8.7|77.3|
  |decode_asr_ctc_asr_model_valid.cer_ctc.ave/test|1155|27500|92.7|4.9|2.3|1.1|8.3|70.6|
  
  ### CER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_ctc_asr_model_valid.cer_ctc.ave/dev|466|78259|97.2|0.9|1.9|1.2|4.0|77.3|
  |decode_asr_ctc_asr_model_valid.cer_ctc.ave/test|1155|145066|97.1|0.9|2.0|1.1|4.0|70.6|
  
  ### TER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_ctc_asr_model_valid.cer_ctc.ave/dev|466|28296|94.7|3.1|2.2|1.2|6.5|77.3|
  |decode_asr_ctc_asr_model_valid.cer_ctc.ave/test|1155|52113|95.0|2.7|2.2|1.1|6.1|70.6|
  
  ## ASR config
  
  <details><summary>expand</summary>
  
  ```
  config: conf/tuning/train_asr_ctc_e_branchformer_e12_mlp1024_linear1024.yaml
  print_config: false
  log_level: INFO
  dry_run: false
  iterator_type: sequence
  output_dir: exp/asr_train_asr_ctc_e_branchformer_e12_mlp1024_linear1024_raw_en_bpe500_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: 47545
  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
      - cer_ctc
      - min
  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: 50000000
  valid_batch_bins: null
  train_shape_file:
  - exp/asr_stats_raw_en_bpe500_sp/train/speech_shape
  - exp/asr_stats_raw_en_bpe500_sp/train/text_shape.bpe
  valid_shape_file:
  - exp/asr_stats_raw_en_bpe500_sp/valid/speech_shape
  - exp/asr_stats_raw_en_bpe500_sp/valid/text_shape.bpe
  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/train_sp/wav.scp
      - speech
      - kaldi_ark
  -   - dump/raw/train_sp/text
      - text
      - text
  valid_data_path_and_name_and_type:
  -   - dump/raw/dev/wav.scp
      - speech
      - kaldi_ark
  -   - dump/raw/dev/text
      - text
      - text
  allow_variable_data_keys: false
  max_cache_size: 0.0
  max_cache_fd: 32
  valid_max_cache_size: null
  optim: adam
  optim_conf:
      lr: 0.002
      weight_decay: 1.0e-06
  scheduler: warmuplr
  scheduler_conf:
      warmup_steps: 15000
  token_list:
  - <blank>
  - <unk>
  - s
  - ▁the
  - t
  - ▁a
  - ▁and
  - ▁to
  - d
  - e
  - ▁of
  - ''''
  - n
  - ing
  - ▁in
  - ▁i
  - ▁that
  - i
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  - l
  - p
  - m
  - y
  - o
  - ▁it
  - ▁we
  - c
  - u
  - ▁you
  - ed
  - ▁
  - r
  - ▁is
  - re
  - ▁this
  - ar
  - g
  - ▁so
  - al
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  - ▁f
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  - ic
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  - 