readme: ---
  tags:
  - espnet
  - audio
  - automatic-speech-recognition
  language: zh
  datasets:
  - aishell
  license: cc-by-4.0
  ---
  
  ## ESPnet2 ASR model 
  
  ### `pyf98/aishell_e_branchformer`
  
  This model was trained by Yifan Peng using aishell 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 89567acf6047737820aef96d2dd2e611825c8b1e
  pip install -e .
  cd egs2/aishell/asr1
  ./run.sh --skip_data_prep false --skip_train true --download_model pyf98/aishell_e_branchformer
  ```
  
  <!-- Generated by scripts/utils/show_asr_result.sh -->
  # RESULTS
  ## Environments
  - date: `Sun Dec 18 12:21:46 CST 2022`
  - python version: `3.9.15 (main, Nov 24 2022, 14:31:59)  [GCC 11.2.0]`
  - espnet version: `espnet 202209`
  - pytorch version: `pytorch 1.12.1`
  - Git hash: `26f432bc859e5e40cac1a86042d498ba7baffbb0`
    - Commit date: `Fri Dec 9 02:16:01 2022 +0000`
  
  ## asr_train_asr_e_branchformer_e12_mlp1024_linear1024_mactrue_amp_raw_zh_char_sp
  ### WER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_branchformer_asr_model_valid.acc.ave/dev|14326|14326|66.9|33.1|0.0|0.0|33.1|33.1|
  |decode_asr_branchformer_asr_model_valid.acc.ave/test|7176|7176|65.4|34.6|0.0|0.0|34.6|34.6|
  
  ### CER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  |decode_asr_branchformer_asr_model_valid.acc.ave/dev|14326|205341|95.9|4.0|0.1|0.1|4.2|33.1|
  |decode_asr_branchformer_asr_model_valid.acc.ave/test|7176|104765|95.6|4.3|0.1|0.1|4.5|34.6|
  
  ### TER
  
  |dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
  |---|---|---|---|---|---|---|---|---|
  
  ## ASR config
  
  <details><summary>expand</summary>
  
  ```
  config: conf/tuning/train_asr_e_branchformer_e12_mlp1024_linear1024_mactrue_amp.yaml
  print_config: false
  log_level: INFO
  dry_run: false
  iterator_type: sequence
  output_dir: exp/asr_train_asr_e_branchformer_e12_mlp1024_linear1024_mactrue_amp_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: 39475
  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: 60
  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: 25000000
  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
      - kaldi_ark
  -   - dump/raw/train_sp/text
      - text
      - text
  valid_data_path_and_name_and_type:
  -   - dump/raw/dev/wav.scp
      - speech
      - kaldi_ark
  -   - 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: 0.001
      weight_decay: 1.0e-06
  scheduler: warmuplr
  scheduler_conf:
      warmup_steps: 35000
  token_list:
  - <blank>
  - <unk>
  - 的
  - 一
  - 在
  - 十
  - 中
  - 是
  - 人
  - 有
  - 二
  - 上
  - 了
  - 不
  - 国
  - 市
  - 大
  - 业
  - 为
  - 年
  - 三
  - 发
  - 个
  - 分
  - 出
  - 会
  - 公
  - 行
  - 地
  - 成
  - 这
  - 和
  - 到
  - 五
  - 产
  - 时
  - 对
  - 房
  - 百
  - 能
  - 场
  - 来
  - 以
  - 新
  - 之
  - 日
  - 者
  - 将
  - 现
  - 四
  - 要
  - 家
  - 资
  - 多
  - 月
  - 也
  - 方
  - 后
  - 机
  - 下
  - 前
  - 零
  - 比
  - 于
  - 生
  - 点
  - 开
  - 动
  - 高
  - 经
  - 进
  - 报
  - 体
  - 赛
  - 子
  - 万
  - 车
  - 用
  - 金
  - 司
  - 可
  - 被
  - 过
  - 手
  - 本
  - 作
  - 自
  - 全
  - 八
  - 六
  - 最
  - 价
  - 目
  - 电
  - 部
  - 交
  - 九
  - 七
  - 面
  - 我
  - 企
  - 加
  - 小
  - 度
  - 实
  - 同
  - 城
  - 工
  - 其
  - 力
  - 定
  -