readme: ---
  tags:
  - espnet
  - audio
  - automatic-speech-recognition
  language: zh
  datasets:
  - aidatatang_200zh
  license: cc-by-4.0
  ---
  
  ## ESPnet2 ASR model 
  
  ### `pyf98/aidatatang_200zh_e_branchformer`
  
  This model was trained by Yifan Peng using aidatatang_200zh 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 7a203d55543df02f0369d5608cd6f3033119a135
  pip install -e .
  cd egs2/aidatatang_200zh/asr1
  ./run.sh --skip_data_prep false --skip_train true --download_model pyf98/aidatatang_200zh_e_branchformer
  ```
  
  <!-- Generated by scripts/utils/show_asr_result.sh -->
  # RESULTS
  ## Environments
  - date: `Mon Dec 26 19:46:01 EST 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: `7a203d55543df02f0369d5608cd6f3033119a135`
    - Commit date: `Fri Dec 23 00:58:49 2022 +0000`
  
  ## asr_train_asr_e_branchformer_linear1024_raw_zh_char_sp
  ### WER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_lm_lm_train_lm_transformer_zh_char_valid.loss.ave_asr_model_valid.acc.ave/dev|24216|24216|81.6|18.4|0.0|0.0|18.4|18.4|
  |decode_asr_lm_lm_train_lm_transformer_zh_char_valid.loss.ave_asr_model_valid.acc.ave/test|48144|48144|79.2|20.8|0.0|0.0|20.8|20.8|
  
  ### CER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_lm_lm_train_lm_transformer_zh_char_valid.loss.ave_asr_model_valid.acc.ave/dev|24216|234524|96.6|3.0|0.4|0.1|3.6|18.4|
  |decode_asr_lm_lm_train_lm_transformer_zh_char_valid.loss.ave_asr_model_valid.acc.ave/test|48144|468933|95.9|3.6|0.4|0.2|4.2|20.8|
  
  ### TER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  
  ## ASR config
  
  <details><summary>expand</summary>
  
  ```
  config: conf/train_asr_e_branchformer_linear1024.yaml
  print_config: false
  log_level: INFO
  dry_run: false
  iterator_type: sequence
  output_dir: exp/asr_train_asr_e_branchformer_linear1024_raw_zh_char_sp
  ngpu: 1
  seed: 0
  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: 35187
  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
  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: 16000000
  valid_batch_bins: null
  train_shape_file:
  - exp/asr_stats_raw_zh_char_sp/train/speech_shape
  - exp/asr_stats_raw_zh_char_sp/train/text_shape.char
  valid_shape_file:
  - exp/asr_stats_raw_zh_char_sp/valid/speech_shape
  - exp/asr_stats_raw_zh_char_sp/valid/text_shape.char
  batch_type: numel
  valid_batch_type: null
  fold_length:
  - 51200
  - 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
      - sound
  -   - dump/raw/train_sp/text
      - text
      - text
  valid_data_path_and_name_and_type:
  -   - dump/raw/dev/wav.scp
      - speech
      - sound
  -   - 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: 0.0005
  scheduler: warmuplr
  scheduler_conf:
      warmup_steps: 30000
  token_list:
  - <blank>
  - <unk>
  - 我
  - 的
  - 你
  - 么
  - 不
  - 是
  - 了
  - 一
  - 有
  - 天
  - 什
  - 好
  - 在
  - 个
  - 怎
  - 吗
  - 话
  - 要
  - 给
  - 电
  - 上
  - 没
  - 人
  - 说
  - 到
  - 啊
  - 就
  - 这
  - 时
  - 来
  - 下
  - 想
  - 打
  - 点
  - 去
  - 还
  - 看
  - 道
  - 多
  - 明
  - 那
  - 知
  - 以
  - 今
  - 能
  - 会
  - 哪
  - 都
  - 可
  - 大
  - 吧
  - 机
  - 样
  - 里
  - 十
  - 现
  - 们
  - 过
  - 吃
  - 开
  - 家
  - 回
  - 发
  - 中
  - 呢
  - 听
  - 候
  - 为
  - 也
  - 日
  - 爱
  - 歌
  - 三
  - 起
  - 小
  - 二
  - 心
  - 子
  - 手
  - 生
  - 最
  - 儿
  - 学
  - 放
  - 信
  - 女
  - 号
  - 几
  