This model was trained by ftshijt using aishell3/tts1 recipe in <a href="https://github.com/espnet/espnet/">espnet</a>. <p> </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"> See ESPNet repo for how to use pre-trained models </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
- 240000 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_no_dev/text
- text
- text
-
- dump/raw/train_no_dev/wav.scp
- speech
- sound
-
- dump/xvector/train_no_dev/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
- i4
- zh
- l
- x
- e
- b
- g
- i1
- h
- q
- m
- u4
- t
- z
- ch
- i3
- i2
- f
- s
- n
- r
- ian4
- e4
- ong1
- en2
- ai4
- k
- ing2
- a1
- iou3
- uo3
- ao4
- u3
- ui4
- p
- e2
- an1
- eng2
- c
- in1
- ai2
- an4
- ian2
- ing1
- ai3
- ang4
- ao3
- ian1
- uo4
- ian3
- iao4
- ang1
- u2
- ü4
- u1
- a4
- eng1
- ing4
- üan2
- ie4
- en1
- iu4
- uei4
- ou4
- er4
- e1
- ei4
- an3
- ong2
- uo2
- ang3
- ou1
- ou3
- ong4
- eng4
- an2
- iang4
- a3
- iang1
- ia1
- iao1
- uan4
- ia4
- iu3
- ang2
- uo1
- ei3
- e3
- in4
- iang3
- ü1
- uan1
- en3
- iao3
- ie3
- ao1
- ai1
- ü2
- ing3
- er2
- ü3
- uan3
- üe4
- in3
- en
- ei2
- üe2
- ie2
- en4
- ua4
- in2
- iu2
- uan2
- a2
- ie1
- ou2
- ui1
- iang2
- ong3
- i
- uang3
- eng3
- ün4
- uang4
- uai4
- iong4
- v3
- iou2
- ui2
- un1
- üan4
- uang1
- ei1
- uang2
- o2
- a
- ao2
- iao2
- ui3
- un4
- o1
- ua2
- un2
- uen2
- iu1
- v4
- ua1
- uei1
- üan3
- ün1
- üe1
- ün2
- uen4
- uei3
- uei2
- un3
- iou4
- o4
- er3
- uen1
- iong3
- iou1
- ia3
- üan1
- ia2
- iong1
- üe3
- uen3
- ve4
- iong2
- uai2
- uai1
- ua3
- ün3
- er
- uai3
- ia
- o3
- v2
- o
- ueng1
- ei
- '2'
- ua
- io1
- <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: 2048 hop_length: 300 win_length: 1200 fs: 24000 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_residual: false spk_embed_dim: 512 spk_embed_integration_type: add use_gst: true gst_heads: 4 gst_tokens: 16 dropout_rate: 0.5 zoneout_rate: 0.1 reduction_factor: 1 use_masking: true bce_pos_weight: 10.0 use_guided_attn_loss: true guided_attn_loss_sigma: 0.4 guided_attn_loss_lambda: 1.0 pitch_extract: null pitch_extract_conf: {} pitch_normalize: null pitch_normalize_conf: {} energy_extract: null energy_extract_conf: {} energy_normalize: null energy_normalize_conf: {} required:
- output_dir
- token_list version: 0.10.2a1 distributed: false</code></pre></li> </ul>