readme: ---
  tags:
  - espnet
  - audio
  - automatic-speech-recognition
  language: en
  datasets:
  - slue-voxceleb
  license: cc-by-4.0
  ---
  
  ## ESPnet2 ASR model 
  
  ### `espnet/siddhana_slue_asr_train_asr_conformer_raw_en_word_valid.acc.ave_10best`
  
  This model was trained by Siddhant using slue-voxceleb recipe in [espnet](https://github.com/espnet/espnet/).
  
  ### Demo: How to use in ESPnet2
  
  ```bash
  cd espnet
  git checkout 17758ad804fd7c4b6f88ef5601f475a241dc4605
  pip install -e .
  cd egs2/slue-voxceleb/asr1
  ./run.sh --skip_data_prep false --skip_train true --download_model espnet/siddhana_slue_asr_train_asr_conformer_raw_en_word_valid.acc.ave_10best
  ```
  
  <!-- Generated by scripts/utils/show_asr_result.sh -->
  # RESULTS
  ## Environments
  - date: `Tue Dec 28 12:28:28 EST 2021`
  - python version: `3.9.5 (default, Jun  4 2021, 12:28:51) [GCC 7.5.0]`
  - espnet version: `espnet 0.10.3a2`
  - pytorch version: `pytorch 1.8.1+cu102`
  - Git hash: `6bf3c2a4f138d35331634d2e879bbc5c32a5266e`
    - Commit date: `Mon Dec 22 15:41:32 EST 2021`
  
  
  ## Using Conformer based encoder and Transformer based decoder with spectral augmentation and predicting transcript along with intent
  - ASR config: [conf/train_asr.yaml](conf/tuning/train_asr_conformer.yaml)
  - token_type: word
  
  |dataset|Snt|Intent Classification Accuracy (%)|Intent Classification Macro F1 (%)|
  |---|---|---|---|
  |inference_asr_model_valid.acc.ave_10best/devel|955|80.2|29.7|
  
  ### Detailed Classification Report
  
  |dataset|Label|Snt|Prec|Recall|F1|
  |---|---|---|---|---|---|
  |inference_asr_model_valid.acc.ave_10best/devel|Neutral|784|85|93|89|
  |inference_asr_model_valid.acc.ave_10best/devel|Positive|167|40|24|30|
  |inference_asr_model_valid.acc.ave_10best/devel|Negative|3|0|0|0|
  |inference_asr_model_valid.acc.ave_10best/devel|Mixed|1|0|0|0|
  
  ## ASR config
  
  <details><summary>expand</summary>
  
  ```
  config: conf/tuning/train_asr_conformer.yaml
  print_config: false
  log_level: INFO
  dry_run: false
  iterator_type: sequence
  output_dir: exp/asr_train_asr_conformer_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
  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_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: []
  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/devel/wav.scp
      - speech
      - sound
  -   - dump/raw/devel/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>
  - ▁i
  - s
  - ▁and
  - ''''
  - ▁the
  - ▁a
  - ▁to
  - ▁it
  - Neutral
  - ▁you
  - ▁that
  - ▁of
  - t
  - ing
  - ▁in
  - ▁was
  - ed
  - ▁uh
  - ▁know
  - e
  - m
  - ▁he
  - y
  - er
  - ▁so
  - ▁we
  - re
  - a
  - o
  - d
  - ▁um
  - i
  - ▁s
  - c
  - ▁like
  - n
  - ▁is
  - ▁be
  - ▁f
  - ▁but
  - ▁c
  - Positive
  - en
  - l
  - ve
  - ▁just
  - ▁m
  - st
  - ▁they
  - le
  - an
  - ▁on
  - ▁p
  - u
  - ▁my
  - ar
  - p
  - ▁this
  - ▁for
  - ▁b
  - ▁think
  - in
  - ▁with
  - g
  - or
  - ▁h
  - r
  - ly
  - w
  - ▁me
  - ▁d
  - ▁e
  - ▁have
  - ▁she
  - it
  - ▁t
  - ▁what
  - b
  - ▁st
  - al
  - es
  - ▁there
  - ▁really
  - ic
  - ▁g
  - ▁as
  - ▁w
  - ▁l
  - ▁do
  - ll
  - v
  - ▁all
  - at
  - 'on'
  - as
  - ▁about
  - h
  - ▁not
  - ▁re
  - ▁o
  - ▁at
  - k
  - ▁don
  - ▁had
  - ▁when
  - ou
  - ent
  - is
  - ra
  - ▁who
  - ri
  - ▁go
  - se
  - f
  - ▁out
  - ▁get
  - ▁an
  - ▁people
  - nd
  - ▁kind
  - ▁very
  - ce
  - ▁because
  - ▁are
  - ion
  - ▁some
  - et
  - ▁can
  - ge
  - ▁or
  - me
  - ▁up
  - ▁n
  - ▁if
  - ▁no
  - ▁one
  - ▁were
  - ct
  - ▁mean
  - ad
  - ▁time
  - ▁ch
  - ▁then
  - ro
  - ▁ex
  - ▁mo
  - ▁her
  - ▁every
  - ▁would
  - ▁co
  - ▁work
  - ir
  - ▁sh
  - ay
  - ▁se
  - ol
  - ver
  - ▁su
  - ▁got
  - ▁k
  - 