readme: ---
  tags:
  - espnet
  - audio
  - automatic-speech-recognition
  language: en
  datasets:
  - stop
  license: cc-by-4.0
  ---
  
  ## ESPnet2 ASR model 
  
  ### `espnet/stop_hubert_slu_raw_en_bpe500`
  
  This model was trained by Siddhant using stop recipe in [espnet](https://github.com/espnet/espnet/).
  
  ### Demo: How to use in ESPnet2
  
  ```bash
  cd espnet
  git checkout 11890fdd9dd872edc50ce8eb7660d746c6ee160e
  pip install -e .
  cd egs2/stop/asr3
  ./run.sh --skip_data_prep false --skip_train true --download_model espnet/stop_hubert_slu_raw_en_bpe500
  ```
  
  <!-- Generated by scripts/utils/show_asr_result.sh -->
  # RESULTS
  ## Environments
  - date: `Sun Dec 25 13:33:10 EST 2022`
  - python version: `3.9.5 (default, Jun  4 2021, 12:28:51)  [GCC 7.5.0]`
  - espnet version: `espnet 202205`
  - pytorch version: `pytorch 1.13.0+cu116`
  - Git hash: `11890fdd9dd872edc50ce8eb7660d746c6ee160e`
    - Commit date: `Sat Jun 18 17:05:39 2022 -0400`
  
  ## asr_train_asr2_hubert_lr0.002_raw_en_bpe500
  ### WER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_asr_model_valid.acc.ave_10best/test|75636|728701|93.9|3.2|2.9|3.1|9.1|29.8|
  |decode_asr_asr_model_valid.acc.ave_10best/valid|33384|322094|0.0|0.0|100.0|0.0|100.0|100.0|
  |inference_asr_model_valid.acc.ave_10best/test|75636|728701|93.9|3.3|2.8|3.2|9.4|30.6|
  |inference_asr_model_valid.acc.ave_10best/valid|33384|322094|0.0|0.0|100.0|0.0|100.0|100.0|
  
  ### CER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_asr_model_valid.acc.ave_10best/test|75636|5745269|95.9|0.9|3.2|3.2|7.3|29.8|
  |decode_asr_asr_model_valid.acc.ave_10best/valid|33384|2537594|0.0|0.0|100.0|0.0|100.0|100.0|
  |inference_asr_model_valid.acc.ave_10best/test|75636|5745269|95.9|1.0|3.1|3.3|7.4|30.6|
  |inference_asr_model_valid.acc.ave_10best/valid|33384|2537594|0.0|0.0|100.0|0.0|100.0|100.0|
  
  ### TER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_asr_model_valid.acc.ave_10best/test|75636|2091389|95.1|1.5|3.4|3.1|8.0|29.8|
  |decode_asr_asr_model_valid.acc.ave_10best/valid|33384|921077|0.0|0.0|100.0|0.0|100.0|100.0|
  |inference_asr_model_valid.acc.ave_10best/test|75636|2091389|95.2|1.5|3.3|3.3|8.1|30.6|
  |inference_asr_model_valid.acc.ave_10best/valid|33384|921077|0.0|0.0|100.0|0.0|100.0|100.0|
  
  ## ASR config
  
  <details><summary>expand</summary>
  
  ```
  config: conf/train_asr2_hubert_lr0.002.yaml
  print_config: false
  log_level: INFO
  dry_run: false
  iterator_type: sequence
  output_dir: exp/asr_train_asr2_hubert_lr0.002_raw_en_bpe500
  ngpu: 1
  seed: 0
  num_workers: 1
  num_att_plot: 3
  dist_backend: nccl
  dist_init_method: env://
  dist_world_size: 4
  dist_rank: 0
  local_rank: 0
  dist_master_addr: localhost
  dist_master_port: 57197
  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: 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:
  - frontend.upstream
  num_iters_per_epoch: null
  batch_size: 128
  valid_batch_size: null
  batch_bins: 1000000
  valid_batch_bins: null
  train_shape_file:
  - exp/asr_stats_raw_en_bpe500/train/speech_shape
  - exp/asr_stats_raw_en_bpe500/train/text_shape.bpe
  valid_shape_file:
  - exp/asr_stats_raw_en_bpe500/valid/speech_shape
  - exp/asr_stats_raw_en_bpe500/valid/text_shape.bpe
  batch_type: folded
  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/wav.scp
      - speech
      - sound
  -   - dump/raw/train/text
      - text
      - text
  valid_data_path_and_name_and_type:
  -   - dump/raw/valid/wav.scp
      - speech
      - sound
  -   - dump/raw/valid/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: 0.0004
      weight_decay: 1.0e-06
  scheduler: warmuplr
  scheduler_conf:
      warmup_steps: 25000
  token_list:
  - <blank>
  - <unk>
  - ▁[
  - ':'
  - ▁]
  - _
  - SL
  - IN
  - GET
  - S
  - TIME
  - DATE
  - ▁THE
  - ▁TO
  - ▁FOR
  - ▁
  - E
  - LOCATION
  - A
  - WEATHER
  - O
  - ▁ME
  - MUSIC
  - ▁MY
  - CREATE
  - ALARM
  - Y
  - D
  - ▁I
  - T
  - ▁AT
  - I
  - ▁A
  - TIMER
  - ▁IS
  - U
  - ▁IN
  - ▁ON
  - EVENT
  - M
  - ▁TIMER
  - TODO
  - REMINDER
  - R
  - ▁PM
  - P
  - ING
  - ▁WHAT
  - ▁THIS
  - ▁TODAY
  - ▁AM
  - N
  - ▁ALARM