readme: ---
  tags:
  - espnet
  - audio
  - automatic-speech-recognition
  language: en
  datasets:
  - harpervalley
  license: cc-by-4.0
  ---
  
  ## ESPnet2 ASR model 
  
  ### `espnet/YushiUeda_harpervalley_train_asr_hubert_raw_en_word`
  
  This model was trained by YushiUeda using harpervalley recipe in [espnet](https://github.com/espnet/espnet/).
  
  ### Demo: How to use in ESPnet2
  
  ```bash
  cd espnet
  git checkout 0b1d15ebe0c36efcdf06d1b2e32361e3c8846cf6
  pip install -e .
  cd egs2/harpervalley/asr1
  ./run.sh --skip_data_prep false --skip_train true --download_model espnet/YushiUeda_harpervalley_train_asr_hubert_raw_en_word
  ```
  
  <!-- Generated by scripts/utils/show_asr_result.sh -->
  # RESULTS
  ## Environments
  - date: `Sat Apr 23 12:20:53 EDT 2022`
  - python version: `3.7.11 (default, Jul 27 2021, 14:32:16)  [GCC 7.5.0]`
  - espnet version: `espnet 0.10.7a1`
  - pytorch version: `pytorch 1.9.0+cu102`
  - Git hash: `0b1d15ebe0c36efcdf06d1b2e32361e3c8846cf6`
    - Commit date: `Tue Apr 5 10:46:40 2022 -0400`
  
  ## asr_train_asr_hubert_raw_en_word
  - config [conf/tuning/train_asr_hubert.yaml](conf/tuning/train_asr_hubert.yaml)
  - token_type word
  
  |dataset|Snt|Intent Classification (%)|
  |---|---|---|
  |inference_asr_model_valid.acc.ave_10best/test|1028|46.0|
  |inference_asr_model_valid.acc.ave_10best/valid|1430|46.6|
  
  ## ASR config
  
  <details><summary>expand</summary>
  
  ```
  config: conf/tuning/train_asr_hubert.yaml
  print_config: false
  log_level: INFO
  dry_run: false
  iterator_type: sequence
  output_dir: exp/asr_train_asr_hubert_raw_en_word
  ngpu: 1
  seed: 0
  num_workers: 1
  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: 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: 20
  valid_batch_size: null
  batch_bins: 1000000
  valid_batch_bins: null
  train_shape_file:
  - exp/asr_stats_raw_en_word/train/speech_shape
  - exp/asr_stats_raw_en_word/train/text_shape.word
  valid_shape_file:
  - exp/asr_stats_raw_en_word/valid/speech_shape
  - exp/asr_stats_raw_en_word/valid/text_shape.word
  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: 0.0002
  scheduler: warmuplr
  scheduler_conf:
      warmup_steps: 25000
  token_list:
  - <blank>
  - <unk>
  - is
  - you
  - i
  - my
  - can
  - name
  - help
  - a
  - pay_bill
  - to
  - the
  - your
  - for
  - thank
  - today
  - transfer_money
  - what
  - order_checks
  - schedule_appointment
  - reset_password
  - check_balance
  - day
  - and
  - valley
  - harper
  - like
  - account
  - how
  - have
  - with
  - bank
  - national
  - there
  - this
  - anything
  - else
  - replace_card
  - would
  - hello
  - get_branch_hours
  - hi
  - great
  - calling
  - one
  - okay
  - that
  - five
  - nine
  - address
  - 'no'
  - dollars
  - appointment
  - m
  - amount
  - card
  - uh
  - been
  - three
  - eight
  - has
  - two
  - new
  - four
  - bill
  - seven
  - all
  - check
  - it
  - company
  - be
  - savings
  - phone
  - that's
  - '[noise]'
  - need
  - checking
  - six
  - hundred
  - balance
  - bye
  - zero
  - transfer
  - alright
  - are
  - branch
  - hours
  - was
  - from
  - thirty
  - me
  - michael
  - password
  - reset
  - sent
  - number
  - jennifer
  - elizabeth
  - send
  - p
  - which
  - james
  - mary
  - um
  - robert
  - much
  - linda
  - checkbook
  - patricia
  - john
  - credit
  - so
  - david
  - repeat
  - pay
  - schedule
  - will
  - too
  - local
  - an
  - of
  - street
  - time
  - debit
  - '[unk]'
  - lost
  - forty
  - at
  - please
  - money
  - gonna
  - between
  - accounts
  - zip
  - we
  - home
  - that'll
  - ordered
  - replacement
  - code
  - johnson
  - scheduled
  - smart
  - replace
  - rodriguez
  - wilson
  - link
  - do
  - source
  - williams
  - i've
  - miller
  - jones
  - davis
  - fossil
  - gas
  - electric
  - brown
  - uhm
  - transferred
  - payment
  - very
  - needed
  - i'd
  - main
  - it's
  - garcia
  - i'm
  - nope
  -