Published September 10, 2021
| Version v1
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Open
ESPnet2 pretrained model, kan-bayashi/csmsc_tts_train_vits_raw_phn_pypinyin_g2p_phone_train.total_count.ave, fs=22050, lang=zh
Creators
Description
This model was trained by kan-bayashi using csmsc/tts1 recipe in espnet.
- Python API
See https://github.com/espnet/espnet_model_zoo
- Evaluate in the recipe
git clone https://github.com/espnet/espnet cd espnet git checkout 628b46282537ce532d613d6bafb75e826e8455de pip install -e . cd egs2/csmsc/tts1 # Download the model file here ./run.sh --skip_data_prep false --skip_train true --download_model kan-bayashi/csmsc_tts_train_vits_raw_phn_pypinyin_g2p_phone_train.total_count.ave
- Config
config: ./conf/tuning/train_vits.yaml print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/tts_train_vits_raw_phn_pypinyin_g2p_phone ngpu: 1 seed: 777 num_workers: 4 num_att_plot: 3 dist_backend: nccl dist_init_method: env:// dist_world_size: 4 dist_rank: 0 local_rank: 0 dist_master_addr: localhost dist_master_port: 41492 dist_launcher: null multiprocessing_distributed: true unused_parameters: true sharded_ddp: false cudnn_enabled: true cudnn_benchmark: true cudnn_deterministic: false collect_stats: false write_collected_feats: false max_epoch: 2000 patience: null val_scheduler_criterion: - valid - loss early_stopping_criterion: - valid - loss - min best_model_criterion: - - train - total_count - max keep_nbest_models: 10 grad_clip: -1 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: 50 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: 5000000 valid_batch_bins: null train_shape_file: - exp/tts_stats_raw_linear_spectrogram_phn_pypinyin_g2p_phone/train/text_shape.phn - exp/tts_stats_raw_linear_spectrogram_phn_pypinyin_g2p_phone/train/speech_shape valid_shape_file: - exp/tts_stats_raw_linear_spectrogram_phn_pypinyin_g2p_phone/valid/text_shape.phn - exp/tts_stats_raw_linear_spectrogram_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/22k/raw/tr_no_dev/text - text - text - - dump/22k/raw/tr_no_dev/wav.scp - speech - sound valid_data_path_and_name_and_type: - - dump/22k/raw/dev/text - text - text - - dump/22k/raw/dev/wav.scp - speech - sound allow_variable_data_keys: false max_cache_size: 0.0 max_cache_fd: 32 valid_max_cache_size: null optim: adamw optim_conf: lr: 0.0002 betas: - 0.8 - 0.99 eps: 1.0e-09 weight_decay: 0.0 scheduler: exponentiallr scheduler_conf: gamma: 0.999875 optim2: adamw optim2_conf: lr: 0.0002 betas: - 0.8 - 0.99 eps: 1.0e-09 weight_decay: 0.0 scheduler2: exponentiallr scheduler2_conf: gamma: 0.999875 generator_first: false token_list: - - - d - sh - j - l - 。 - zh - , - i4 - x - h - b - e - g - t - m - z - q - i1 - i3 - ch - u4 - n - f - i2 - r - k - s - e4 - ai4 - a1 - c - p - ian4 - uo3 - ao3 - ai2 - ao4 - an4 - u3 - ong1 - ing2 - en2 - u2 - e2 - ui4 - ian2 - iou3 - ang4 - u1 - iao4 - uo4 - eng2 - a4 - in1 - ang1 - eng1 - ou3 - ian1 - ou4 - ing1 - uo1 - an1 - ian3 - ie3 - a3 - an3 - ing4 - an2 - ü4 - iao3 - ei4 - ong2 - en1 - uei4 - üan2 - ang2 - ang3 - iu4 - iang4 - ai3 - ao1 - ou1 - eng4 - iang3 - en3 - ai1 - ong4 - ie4 - e3 - ia1 - uo2 - ia4 - ü3 - uan1 - er2 - ei3 - ei2 - iang1 - ing3 - en4 - ü2 - uan3 - e1 - in2 - iao1 - i - in4 - ie1 - ong3 - iang2 - ie2 - uan4 - a2 - ui3 - eng3 - uan2 - üe4 - uai4 - ou2 - ? - üe2 - in3 - uang3 - uang1 - iu2 - en - a - ao2 - ua4 - un1 - ui1 - uei2 - iong4 - uang2 - v3 - ui2 - iao2 - uang4 - ü1 - ei1 - o2 - er4 - iou2 - iou4 - ! - ua1 - üan4 - iu3 - un4 - üan3 - ün4 - uen2 - iu1 - un3 - uen4 - un2 - er3 - ün1 - ün2 - o4 - o1 - ua2 - uei1 - uei3 - ia3 - iong3 - ua3 - ia - v4 - üe1 - üan1 - iong1 - ia2 - uai1 - iong2 - iou1 - uai3 - üe3 - uen1 - uen3 - uai2 - o3 - er - ve4 - ou - io1 - ün3 - ueng1 - v2 - uo - ueng4 - o - ua - ei - '2' - ueng3 - ang - P - B - odim: null model_conf: {} use_preprocessor: true token_type: phn bpemodel: null non_linguistic_symbols: null cleaner: null g2p: pypinyin_g2p_phone feats_extract: linear_spectrogram feats_extract_conf: n_fft: 1024 hop_length: 256 win_length: null normalize: null normalize_conf: {} tts: vits tts_conf: generator_type: vits_generator generator_params: hidden_channels: 192 spks: -1 global_channels: -1 segment_size: 32 text_encoder_attention_heads: 2 text_encoder_ffn_expand: 4 text_encoder_blocks: 6 text_encoder_positionwise_layer_type: conv1d text_encoder_positionwise_conv_kernel_size: 3 text_encoder_positional_encoding_layer_type: rel_pos text_encoder_self_attention_layer_type: rel_selfattn text_encoder_activation_type: swish text_encoder_normalize_before: true text_encoder_dropout_rate: 0.1 text_encoder_positional_dropout_rate: 0.0 text_encoder_attention_dropout_rate: 0.1 use_macaron_style_in_text_encoder: true use_conformer_conv_in_text_encoder: false text_encoder_conformer_kernel_size: -1 decoder_kernel_size: 7 decoder_channels: 512 decoder_upsample_scales: - 8 - 8 - 2 - 2 decoder_upsample_kernel_sizes: - 16 - 16 - 4 - 4 decoder_resblock_kernel_sizes: - 3 - 7 - 11 decoder_resblock_dilations: - - 1 - 3 - 5 - - 1 - 3 - 5 - - 1 - 3 - 5 use_weight_norm_in_decoder: true posterior_encoder_kernel_size: 5 posterior_encoder_layers: 16 posterior_encoder_stacks: 1 posterior_encoder_base_dilation: 1 posterior_encoder_dropout_rate: 0.0 use_weight_norm_in_posterior_encoder: true flow_flows: 4 flow_kernel_size: 5 flow_base_dilation: 1 flow_layers: 4 flow_dropout_rate: 0.0 use_weight_norm_in_flow: true use_only_mean_in_flow: true stochastic_duration_predictor_kernel_size: 3 stochastic_duration_predictor_dropout_rate: 0.5 stochastic_duration_predictor_flows: 4 stochastic_duration_predictor_dds_conv_layers: 3 vocabs: 202 aux_channels: 513 discriminator_type: hifigan_multi_scale_multi_period_discriminator discriminator_params: scales: 1 scale_downsample_pooling: AvgPool1d scale_downsample_pooling_params: kernel_size: 4 stride: 2 padding: 2 scale_discriminator_params: in_channels: 1 out_channels: 1 kernel_sizes: - 15 - 41 - 5 - 3 channels: 128 max_downsample_channels: 1024 max_groups: 16 bias: true downsample_scales: - 2 - 2 - 4 - 4 - 1 nonlinear_activation: LeakyReLU nonlinear_activation_params: negative_slope: 0.1 use_weight_norm: true use_spectral_norm: false follow_official_norm: false periods: - 2 - 3 - 5 - 7 - 11 period_discriminator_params: in_channels: 1 out_channels: 1 kernel_sizes: - 5 - 3 channels: 32 downsample_scales: - 3 - 3 - 3 - 3 - 1 max_downsample_channels: 1024 bias: true nonlinear_activation: LeakyReLU nonlinear_activation_params: negative_slope: 0.1 use_weight_norm: true use_spectral_norm: false generator_adv_loss_params: average_by_discriminators: false loss_type: mse discriminator_adv_loss_params: average_by_discriminators: false loss_type: mse feat_match_loss_params: average_by_discriminators: false average_by_layers: false include_final_outputs: true mel_loss_params: fs: 22050 n_fft: 1024 hop_length: 256 win_length: null window: hann n_mels: 80 fmin: 0 fmax: null log_base: null lambda_adv: 1.0 lambda_mel: 45.0 lambda_feat_match: 2.0 lambda_dur: 1.0 lambda_kl: 1.0 sampling_rate: 22050 cache_generator_outputs: true 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: 0.10.3a1 distributed: true
Files
tts_train_vits_raw_phn_pypinyin_g2p_phone_train.total_count.ave.zip
Files
(373.6 MB)
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Additional details
Related works
- Is supplement to
- https://github.com/espnet/espnet (URL)