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--- |
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tags: |
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- espnet |
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- audio |
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- text-to-speech |
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language: ko |
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datasets: |
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- kss |
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license: cc-by-4.0 |
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--- |
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## ESPnet2 TTS model |
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### `imdanboy/kss_jets` |
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This model was trained by imdanboy using kss recipe in [espnet](https://github.com/espnet/espnet/). |
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### Demo: How to use in ESPnet2 |
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Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html) |
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if you haven't done that already. |
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```bash |
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cd espnet |
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git checkout 967ddbed826a7c90b75be2a7129588442d5cb6af |
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pip install -e . |
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cd egs2/kss/tts1 |
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./run.sh --skip_data_prep false --skip_train true --download_model imdanboy/kss_jets |
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``` |
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## TTS config |
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<details><summary>expand</summary> |
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``` |
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config: conf/tuning/train_jets.yaml |
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print_config: false |
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log_level: INFO |
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dry_run: false |
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iterator_type: sequence |
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output_dir: exp/tts_train_jets_raw_phn_g2pk_no_space |
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ngpu: 1 |
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seed: 777 |
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num_workers: 4 |
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num_att_plot: 3 |
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dist_backend: nccl |
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dist_init_method: env:// |
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dist_world_size: 4 |
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dist_rank: 0 |
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local_rank: 0 |
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dist_master_addr: localhost |
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dist_master_port: 51627 |
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dist_launcher: null |
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multiprocessing_distributed: true |
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unused_parameters: true |
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sharded_ddp: false |
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cudnn_enabled: true |
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cudnn_benchmark: false |
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cudnn_deterministic: false |
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collect_stats: false |
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write_collected_feats: false |
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max_epoch: 1000 |
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patience: null |
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val_scheduler_criterion: |
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- valid |
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- loss |
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early_stopping_criterion: |
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- valid |
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- loss |
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- min |
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best_model_criterion: |
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- - valid |
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- text2mel_loss |
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- min |
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- - train |
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- text2mel_loss |
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- min |
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- - train |
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- total_count |
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- max |
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keep_nbest_models: 5 |
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nbest_averaging_interval: 0 |
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grad_clip: -1 |
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grad_clip_type: 2.0 |
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grad_noise: false |
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accum_grad: 1 |
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no_forward_run: false |
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resume: true |
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train_dtype: float32 |
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use_amp: false |
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log_interval: 50 |
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use_matplotlib: true |
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use_tensorboard: true |
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create_graph_in_tensorboard: false |
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use_wandb: false |
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wandb_project: null |
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wandb_id: null |
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wandb_entity: null |
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wandb_name: null |
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wandb_model_log_interval: -1 |
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detect_anomaly: false |
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pretrain_path: null |
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init_param: [] |
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ignore_init_mismatch: false |
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freeze_param: [] |
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num_iters_per_epoch: 1000 |
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batch_size: 20 |
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valid_batch_size: null |
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batch_bins: 4500000 |
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valid_batch_bins: null |
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train_shape_file: |
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- exp/tts_stats_raw_phn_g2pk_no_space/train/text_shape.phn |
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- exp/tts_stats_raw_phn_g2pk_no_space/train/speech_shape |
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valid_shape_file: |
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- exp/tts_stats_raw_phn_g2pk_no_space/valid/text_shape.phn |
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- exp/tts_stats_raw_phn_g2pk_no_space/valid/speech_shape |
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batch_type: numel |
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valid_batch_type: null |
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fold_length: |
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- 150 |
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- 204800 |
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sort_in_batch: descending |
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sort_batch: descending |
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multiple_iterator: false |
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chunk_length: 500 |
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chunk_shift_ratio: 0.5 |
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num_cache_chunks: 1024 |
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chunk_excluded_key_prefixes: [] |
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train_data_path_and_name_and_type: |
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- - dump/raw/tr_no_dev/text |
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- text |
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- text |
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- - dump/raw/tr_no_dev/wav.scp |
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- speech |
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- sound |
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- - exp/tts_stats_raw_phn_g2pk_no_space/train/collect_feats/pitch.scp |
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- pitch |
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- npy |
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- - exp/tts_stats_raw_phn_g2pk_no_space/train/collect_feats/energy.scp |
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- energy |
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- npy |
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valid_data_path_and_name_and_type: |
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- - dump/raw/dev/text |
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- text |
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- text |
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- - dump/raw/dev/wav.scp |
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- speech |
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- sound |
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- - exp/tts_stats_raw_phn_g2pk_no_space/valid/collect_feats/pitch.scp |
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- pitch |
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- npy |
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- - exp/tts_stats_raw_phn_g2pk_no_space/valid/collect_feats/energy.scp |
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- energy |
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- npy |
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allow_variable_data_keys: false |
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max_cache_size: 0.0 |
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max_cache_fd: 32 |
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valid_max_cache_size: null |
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exclude_weight_decay: false |
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exclude_weight_decay_conf: {} |
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optim: adamw |
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optim_conf: |
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lr: 0.0002 |
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betas: |
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- 0.8 |
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- 0.99 |
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eps: 1.0e-09 |
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weight_decay: 0.0 |
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scheduler: exponentiallr |
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scheduler_conf: |
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gamma: 0.999875 |
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optim2: adamw |
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optim2_conf: |
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lr: 0.0002 |
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betas: |
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- 0.8 |
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- 0.99 |
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eps: 1.0e-09 |
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weight_decay: 0.0 |
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scheduler2: exponentiallr |
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scheduler2_conf: |
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gamma: 0.999875 |
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generator_first: true |
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token_list: |
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- <blank> |
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- <unk> |
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- ᅡ |
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- ᅵ |
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- ᄋ |
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- ᅳ |
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- ᄀ |
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- ᅥ |
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- ᄂ |
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- ᆫ |
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- ᄅ |
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- ᄌ |
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- ᄉ |
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- ᅩ |
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- ᆯ |
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- ᄆ |
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- . |
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- ᅮ |
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- ᄃ |
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- ᄒ |
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- ᅦ |
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- ᆼ |
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- ᅢ |
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- ᄇ |
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- ᅭ |
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- ᅧ |
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- ᄊ |
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- ᆷ |
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- ᄄ |
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- ᆮ |
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- ᄎ |
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- ᄁ |
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- ᆨ |
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- ᄑ |
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- ᄐ |
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- ᅪ |
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- ᄏ |
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- '?' |
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- ᄍ |
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- ᆸ |
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- ᅬ |
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- ᅣ |
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- ᅴ |
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- ᅯ |
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- ᅨ |
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- ᄈ |
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- ᅱ |
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- ᅲ |
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- ᅫ |
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- ',' |
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- '!' |
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- ᅤ |
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- ':' |
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- ᅰ |
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- '''' |
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- '-' |
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- '"' |
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- / |
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- I |
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- M |
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- F |
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- E |
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- S |
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- C |
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- A |
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- B |
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- ㅇ |
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- <sos/eos> |
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odim: null |
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model_conf: {} |
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use_preprocessor: true |
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token_type: phn |
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bpemodel: null |
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non_linguistic_symbols: null |
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cleaner: null |
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g2p: g2pk_no_space |
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feats_extract: fbank |
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feats_extract_conf: |
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n_fft: 1024 |
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hop_length: 256 |
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win_length: null |
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fs: 24000 |
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fmin: 80 |
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fmax: 7600 |
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n_mels: 80 |
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normalize: global_mvn |
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normalize_conf: |
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stats_file: exp/tts_stats_raw_phn_g2pk_no_space/train/feats_stats.npz |
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tts: jets |
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tts_conf: |
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generator_type: jets_generator |
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generator_params: |
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adim: 256 |
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aheads: 2 |
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elayers: 4 |
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eunits: 1024 |
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dlayers: 4 |
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dunits: 1024 |
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positionwise_layer_type: conv1d |
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positionwise_conv_kernel_size: 3 |
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duration_predictor_layers: 2 |
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duration_predictor_chans: 256 |
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duration_predictor_kernel_size: 3 |
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use_masking: true |
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encoder_normalize_before: true |
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decoder_normalize_before: true |
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encoder_type: transformer |
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decoder_type: transformer |
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conformer_rel_pos_type: latest |
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conformer_pos_enc_layer_type: rel_pos |
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conformer_self_attn_layer_type: rel_selfattn |
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conformer_activation_type: swish |
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use_macaron_style_in_conformer: true |
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use_cnn_in_conformer: true |
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conformer_enc_kernel_size: 7 |
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conformer_dec_kernel_size: 31 |
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init_type: xavier_uniform |
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transformer_enc_dropout_rate: 0.2 |
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transformer_enc_positional_dropout_rate: 0.2 |
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transformer_enc_attn_dropout_rate: 0.2 |
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transformer_dec_dropout_rate: 0.2 |
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transformer_dec_positional_dropout_rate: 0.2 |
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transformer_dec_attn_dropout_rate: 0.2 |
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pitch_predictor_layers: 5 |
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pitch_predictor_chans: 256 |
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pitch_predictor_kernel_size: 5 |
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pitch_predictor_dropout: 0.5 |
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pitch_embed_kernel_size: 1 |
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pitch_embed_dropout: 0.0 |
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stop_gradient_from_pitch_predictor: true |
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energy_predictor_layers: 2 |
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energy_predictor_chans: 256 |
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energy_predictor_kernel_size: 3 |
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energy_predictor_dropout: 0.5 |
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energy_embed_kernel_size: 1 |
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energy_embed_dropout: 0.0 |
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stop_gradient_from_energy_predictor: false |
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generator_out_channels: 1 |
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generator_channels: 512 |
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generator_global_channels: -1 |
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generator_kernel_size: 7 |
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generator_upsample_scales: |
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- 8 |
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- 8 |
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- 2 |
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- 2 |
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generator_upsample_kernel_sizes: |
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- 16 |
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- 16 |
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- 4 |
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- 4 |
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generator_resblock_kernel_sizes: |
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- 3 |
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- 7 |
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- 11 |
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generator_resblock_dilations: |
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- - 1 |
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- 3 |
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- 5 |
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- - 1 |
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- 3 |
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- 5 |
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- - 1 |
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- 3 |
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- 5 |
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generator_use_additional_convs: true |
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generator_bias: true |
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generator_nonlinear_activation: LeakyReLU |
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generator_nonlinear_activation_params: |
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negative_slope: 0.1 |
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generator_use_weight_norm: true |
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segment_size: 32 |
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idim: 68 |
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odim: 80 |
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discriminator_type: hifigan_multi_scale_multi_period_discriminator |
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discriminator_params: |
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scales: 1 |
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scale_downsample_pooling: AvgPool1d |
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scale_downsample_pooling_params: |
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kernel_size: 4 |
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stride: 2 |
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padding: 2 |
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scale_discriminator_params: |
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in_channels: 1 |
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out_channels: 1 |
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kernel_sizes: |
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- 15 |
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- 41 |
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- 5 |
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- 3 |
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channels: 128 |
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max_downsample_channels: 1024 |
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max_groups: 16 |
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bias: true |
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downsample_scales: |
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- 2 |
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- 2 |
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- 4 |
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- 4 |
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- 1 |
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nonlinear_activation: LeakyReLU |
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nonlinear_activation_params: |
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negative_slope: 0.1 |
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use_weight_norm: true |
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use_spectral_norm: false |
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follow_official_norm: false |
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periods: |
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- 2 |
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- 3 |
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- 5 |
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- 7 |
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- 11 |
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period_discriminator_params: |
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in_channels: 1 |
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out_channels: 1 |
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kernel_sizes: |
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- 5 |
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- 3 |
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channels: 32 |
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downsample_scales: |
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- 3 |
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- 3 |
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- 3 |
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- 3 |
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- 1 |
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max_downsample_channels: 1024 |
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bias: true |
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nonlinear_activation: LeakyReLU |
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nonlinear_activation_params: |
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negative_slope: 0.1 |
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use_weight_norm: true |
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use_spectral_norm: false |
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generator_adv_loss_params: |
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average_by_discriminators: false |
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loss_type: mse |
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discriminator_adv_loss_params: |
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average_by_discriminators: false |
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loss_type: mse |
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feat_match_loss_params: |
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average_by_discriminators: false |
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average_by_layers: false |
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include_final_outputs: true |
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mel_loss_params: |
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fs: 24000 |
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n_fft: 1024 |
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hop_length: 256 |
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win_length: null |
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window: hann |
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n_mels: 80 |
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fmin: 0 |
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fmax: null |
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log_base: null |
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lambda_adv: 1.0 |
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lambda_mel: 45.0 |
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lambda_feat_match: 2.0 |
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lambda_var: 1.0 |
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lambda_align: 1.0 |
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sampling_rate: 24000 |
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cache_generator_outputs: true |
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pitch_extract: dio |
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pitch_extract_conf: |
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reduction_factor: 1 |
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use_token_averaged_f0: false |
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fs: 24000 |
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n_fft: 1024 |
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hop_length: 256 |
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f0max: 400 |
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f0min: 80 |
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pitch_normalize: global_mvn |
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pitch_normalize_conf: |
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stats_file: exp/tts_stats_raw_phn_g2pk_no_space/train/pitch_stats.npz |
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energy_extract: energy |
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energy_extract_conf: |
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reduction_factor: 1 |
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use_token_averaged_energy: false |
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fs: 24000 |
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n_fft: 1024 |
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hop_length: 256 |
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win_length: null |
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energy_normalize: global_mvn |
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energy_normalize_conf: |
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stats_file: exp/tts_stats_raw_phn_g2pk_no_space/train/energy_stats.npz |
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required: |
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- output_dir |
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- token_list |
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version: '202304' |
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distributed: true |
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``` |
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</details> |
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### Citing ESPnet |
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```BibTex |
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@inproceedings{watanabe2018espnet, |
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author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai}, |
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title={{ESPnet}: End-to-End Speech Processing Toolkit}, |
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year={2018}, |
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booktitle={Proceedings of Interspeech}, |
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pages={2207--2211}, |
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doi={10.21437/Interspeech.2018-1456}, |
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url={http://dx.doi.org/10.21437/Interspeech.2018-1456} |
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} |
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@inproceedings{hayashi2020espnet, |
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title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit}, |
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author={Hayashi, Tomoki and Yamamoto, Ryuichi and Inoue, Katsuki and Yoshimura, Takenori and Watanabe, Shinji and Toda, Tomoki and Takeda, Kazuya and Zhang, Yu and Tan, Xu}, |
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booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, |
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pages={7654--7658}, |
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year={2020}, |
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organization={IEEE} |
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} |
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``` |
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or arXiv: |
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```bibtex |
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@misc{watanabe2018espnet, |
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title={ESPnet: End-to-End Speech Processing Toolkit}, |
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author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai}, |
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year={2018}, |
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eprint={1804.00015}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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