readme: ---
  tags:
  - espnet
  - audio
  - text-to-speech
  language: zh
  datasets:
  - thchs30
  license: cc-by-4.0
  inference: false
  ---
  
  
  This model was trained by ftshijt using thchs30/tts1 recipe in <a href="https://github.com/espnet/espnet/">espnet</a>.
  <p>&nbsp;</p>
  <ul>
  <li><strong>Python API</strong><pre><code class="language-python">See https://github.com/espnet/espnet_model_zoo</code></pre></li>
  <li><strong>Evaluate in the recipe</strong><pre>
  <code class="language-bash">Please see ESPNet for how to use pre-trained model
  </pre></li>
  <li><strong>Config</strong><pre><code>config: conf/train.yaml
  print_config: false
  log_level: INFO
  dry_run: false
  iterator_type: sequence
  output_dir: exp/tts_train_raw_phn_pypinyin_g2p_phone
  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: 500
  patience: null
  val_scheduler_criterion:
  - valid
  - loss
  early_stopping_criterion:
  - valid
  - loss
  - min
  best_model_criterion:
  -   - valid
      - loss
      - min
  -   - train
      - loss
      - min
  keep_nbest_models: 5
  grad_clip: 1.0
  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: 500
  batch_size: 20
  valid_batch_size: null
  batch_bins: 3750000
  valid_batch_bins: null
  train_shape_file:
  - exp/tts_stats_raw_phn_pypinyin_g2p_phone/train/text_shape.phn
  - exp/tts_stats_raw_phn_pypinyin_g2p_phone/train/speech_shape
  valid_shape_file:
  - exp/tts_stats_raw_phn_pypinyin_g2p_phone/valid/text_shape.phn
  - exp/tts_stats_raw_phn_pypinyin_g2p_phone/valid/speech_shape
  batch_type: numel
  valid_batch_type: null
  fold_length:
  - 150
  - 204800
  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/text
      - text
      - text
  -   - dump/raw/train/wav.scp
      - speech
      - sound
  -   - dump/xvector/train/xvector.scp
      - spembs
      - kaldi_ark
  valid_data_path_and_name_and_type:
  -   - dump/raw/dev/text
      - text
      - text
  -   - dump/raw/dev/wav.scp
      - speech
      - sound
  -   - dump/xvector/dev/xvector.scp
      - spembs
      - kaldi_ark
  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
      eps: 1.0e-06
      weight_decay: 0.0
  scheduler: null
  scheduler_conf: {}
  token_list:
  - <blank>
  - <unk>
  - ''
  - d
  - sh
  - j
  - zh
  - l
  - i4
  - x
  - b
  - g
  - h
  - e
  - q
  - t
  - m
  - ch
  - i1
  - z
  - u4
  - i2
  - i3
  - n
  - f
  - s
  - r
  - k
  - c
  - p
  - ai4
  - e4
  - a1
  - an4
  - ian4
  - ing2
  - u3
  - ian2
  - ong1
  - e2
  - in1
  - eng2
  - ui4
  - ao4
  - u2
  - iao4
  - üan2
  - en2
  - an1
  - u1
  - ai2
  - ao3
  - ing4
  - eng1
  - iou3
  - ü4
  - uo4
  - üe4
  - ong2
  - ian1
  - ing1
  - uo3
  - ie4
  - ang1
  - uei4
  - ang4
  - an2
  - a4
  - ou4
  - ei4
  - uai4
  - ie3
  - ang3
  - ong4
  - ai3
  - ü2
  - uo2
  - an3
  - ang2
  - ou3
  - er2
  - ou1
  - uo1
  - en1
  - ia1
  - ü3
  - uan1
  - in2
  - iong4
  - ian3
  - iang3
  - a3
  - iang2
  - ia4
  - ü1
  - uan4
  - iao3
  - iang4
  - uen2
  - iang1
  - uan3
  - ai1
  - ie2
  - ei3
  - uan2
  - uang2
  - in4
  - üe2
  - ao1
  - eng3
  - iu4
  - iao1
  - er4
  - iu2
  - in3
  - un1
  - uang1
  - eng4
  - a2
  - uang3
  - en3
  - uang4
  - ong3
  - ing3
  - e3
  - ei2
  - ou2
  - ao2
  - i
  - ün4
  - uei2
  - ua4
  - iou4
  - ui1
  - ua1
  - en4
  - ün2
  - iao2
  - ie1
  - iou2
  - iu3
  - ün1
  - üan4
  - en
  - ei1
  - o2
  - un4
  - ui3
  - iu1
  - üan3
  - e1
  - v3
  - ua2
  - ia2
  - ui2
  - un2
  - o4
  - un3
  - er3
  - ia3
  - iong1
  - uei3
  - o1
  - üe1
  - üan1
  - iong3
  - v4
  - iong2
  - uen4
  - uai2
  - uei1
  - iou1
  - a
  - ua3
  - uen1
  - o3
  - ueng1
  - uai1
  - uen3
  - üe3
  - ou
  - uai3
  - ve4
  - er
  - ün3
  - o
  - ua
  - ia
  - ' l ='
  - <sos/eos>
  odim: null
  model_conf: {}
  use_preprocessor: true
  token_type: phn
  bpemodel: null
  non_linguistic_symbols: null
  cleaner: null
  g2p: pypinyin_g2p_phone
  feats_extract: fbank
  feats_extract_conf:
      n_fft: 1024
      hop_length: 256
      win_length: null
      fs: 16000
      fmin: 80
      fmax: 7600
      n_mels: 80
  normalize: global_mvn
  normalize_conf:
      stats_file: exp/tts_stats_raw_phn_pypinyin_g2p_phone/train/feats_stats.npz
  tts: tacotron2
  tts_conf:
      embed_dim: 512
      elayers: 1
      eunits: 512
      econv_layers: 3
      econv_chans: 512
      econv_filts: 5
      atype: location
      adim: 512
      aconv_chans: 32
      aconv_filts: 15
      cumulate_att_w: true
      dlayers: 2
      dunits: 1024
      prenet_layers: 2
      prenet_units: 256
      postnet_layers: 5
      postnet_chans: 512
      postnet_filts: 5
      output_activation: null
      use_batch_norm: true
      use_concate: true
      use_res