readme: ---
  tags:
  - espnet
  - audio
  - automatic-speech-recognition
  language: en
  datasets:
  - swbd
  license: cc-by-4.0
  ---
  
  ## ESPnet2 ASR model 
  
  ### `pyf98/swbd_conformer`
  
  This model was trained by Yifan Peng using swbd recipe in [espnet](https://github.com/espnet/espnet/).
  
  ### 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 ef3ce328551c12c03284defc757f42df47c46170
  pip install -e .
  cd egs2/swbd/asr1
  ./run.sh --skip_data_prep false --skip_train true --download_model pyf98/swbd_conformer
  ```
  
  <!-- Generated by scripts/utils/show_asr_result.sh -->
  # RESULTS
  ## Environments
  - date: `Tue Dec 27 03:17:13 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: `ef3ce328551c12c03284defc757f42df47c46170`
    - Commit date: `Mon Dec 26 20:34:28 2022 -0500`
  
  ## asr_train_asr_conformer_e12_size256_linear2048_raw_en_bpe2000_sp
  ### WER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_asr_model_valid.acc.ave/eval2000/hyp.callhm.ctm.filt.sys|2628|21594|88.3|8.5|3.2|2.1|13.8|46.8|
  |decode_asr_asr_model_valid.acc.ave/eval2000/hyp.ctm.filt.sys|4459|42989|90.8|6.2|3.0|1.5|10.7|42.4|
  |decode_asr_asr_model_valid.acc.ave/eval2000/hyp.swbd.ctm.filt.sys|1831|21395|93.4|3.9|2.7|0.9|7.5|36.1|
  
  ### CER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_asr_model_valid.acc.ave/eval2000|4322|181952|92.8|3.4|3.8|10.8|18.0|68.1|
  
  ### TER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_asr_model_valid.acc.ave/eval2000|4322|47227|82.6|12.8|4.6|15.3|32.7|68.1|
  
  ## ASR config
  
  <details><summary>expand</summary>
  
  ```
  config: conf/tuning/train_asr_conformer_e12_size256_linear2048.yaml
  print_config: false
  log_level: INFO
  dry_run: false
  iterator_type: sequence
  output_dir: exp/asr_train_asr_conformer_e12_size256_linear2048_raw_en_bpe2000_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: 37605
  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: 100
  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: 40000000
  valid_batch_bins: null
  train_shape_file:
  - exp/asr_stats_raw_en_bpe2000_sp/train/speech_shape
  - exp/asr_stats_raw_en_bpe2000_sp/train/text_shape.bpe
  valid_shape_file:
  - exp/asr_stats_raw_en_bpe2000_sp/valid/speech_shape
  - exp/asr_stats_raw_en_bpe2000_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_nodup_sp/wav.scp
      - speech
      - kaldi_ark
  -   - dump/raw/train_nodup_sp/text
      - text
      - text
  valid_data_path_and_name_and_type:
  -   - dump/raw/train_dev/wav.scp
      - speech
      - kaldi_ark
  -   - dump/raw/train_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: 50000
  token_list:
  - <blank>
  - <unk>
  - ▁i
  - ''''
  - s
  - ▁and
  - ▁the
  - ▁you
  - ▁that
  - ▁a
  - ▁it
  - ▁uh
  - ▁to
  - t
  - ▁of
  - ▁know
  - ▁they
  - '-'
  - ▁in
  - ▁we
  - ']'
  - ▁[
  - ▁yeah
  - ▁have
  - ▁but
  - ▁so
  - ▁was
  - ▁like
  - re
  - ▁um
  - ▁just
  - ▁well
  - ▁do
  - m
  - ▁for
  - ing
  - ▁think
  - ▁don
  - d
  - ▁is
  - ▁there
  - ▁or
  - ▁on
  - ▁be
  - noise
  - ▁what
  - ▁oh
  - laughter
  - ▁my
  - ed
  - ve
  - ▁not
  - ▁really
  - ▁with
  - ▁he
  - n
  - ▁one
  - ▁if
  - ▁are
  - ▁all
  - ▁get
  - ▁right
  - ▁about
  - ▁can
  - ▁because
  - ▁out
  - ▁had
  - ▁up
  - ▁them
  - ▁lot
  - ▁at
  - ▁this
  - ▁would
  - ▁when
  - ▁go
  - ▁some
  - er
  - ▁people
  - ▁no
  - ▁mean
  - ▁kind
  - ▁then
  - a
  - v
  - ▁good
  - e
  - ll
  - ▁now
  - ▁got
  - ▁me
  - p
  - ▁time
  - o
  - ▁she
  - ▁as
  - ▁going
  - y
  - ▁see
  - ▁more
  - ▁were
  - ly
  - ▁been
  - ▁from
  - 