import from zenodo
Browse files- README.md +50 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/100epoch.pth +3 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/config.yaml +355 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_backward_time.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_fake_loss.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_forward_time.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_loss.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_optim_step_time.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_real_loss.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_train_time.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_adv_loss.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_backward_time.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_dur_loss.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_feat_match_loss.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_forward_time.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_kl_loss.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_loss.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_mel_loss.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_optim_step_time.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_train_time.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/gpu_max_cached_mem_GB.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/iter_time.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/optim0_lr0.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/optim1_lr0.png +0 -0
- exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/train_time.png +0 -0
- meta.yaml +8 -0
README.md
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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: ja
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datasets:
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- jvs
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license: cc-by-4.0
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---
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## ESPnet2 TTS pretrained model
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### `kan-bayashi/jvs_jvs010_vits_prosody`
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♻️ Imported from https://zenodo.org/record/5521494/
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This model was trained by kan-bayashi using jvs/tts1 recipe in [espnet](https://github.com/espnet/espnet/).
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### Demo: How to use in ESPnet2
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```python
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# coming soon
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```
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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 {Enrique Yalta Soplin} 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 Enrique Yalta Soplin 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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exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/100epoch.pth
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version https://git-lfs.github.com/spec/v1
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oid sha256:45cbc7be0f3562f52d96ac66b123d6389ccb6047b642bfb5434e6adeedfa6b4d
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size 372549199
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exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/config.yaml
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config: ./conf/tuning/finetune_vits.v2.yaml
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2 |
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print_config: false
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3 |
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log_level: INFO
|
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dry_run: false
|
5 |
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iterator_type: sequence
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6 |
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output_dir: exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody
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ngpu: 1
|
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seed: 777
|
9 |
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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
|
15 |
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local_rank: 0
|
16 |
+
dist_master_addr: localhost
|
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dist_master_port: 41593
|
18 |
+
dist_launcher: null
|
19 |
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multiprocessing_distributed: true
|
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+
unused_parameters: true
|
21 |
+
sharded_ddp: false
|
22 |
+
cudnn_enabled: true
|
23 |
+
cudnn_benchmark: true
|
24 |
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cudnn_deterministic: false
|
25 |
+
collect_stats: false
|
26 |
+
write_collected_feats: false
|
27 |
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max_epoch: 100
|
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patience: null
|
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val_scheduler_criterion:
|
30 |
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- valid
|
31 |
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- loss
|
32 |
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early_stopping_criterion:
|
33 |
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- valid
|
34 |
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- loss
|
35 |
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- min
|
36 |
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best_model_criterion:
|
37 |
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- - train
|
38 |
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- total_count
|
39 |
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- max
|
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keep_nbest_models: 10
|
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grad_clip: -1
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grad_clip_type: 2.0
|
43 |
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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_tensorboard: true
|
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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:
|
60 |
+
- ../../jsut/tts1/exp/tts_train_vits_raw_phn_jaconv_pyopenjtalk_prosody/latest.pth:tts:tts
|
61 |
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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: 5000000
|
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valid_batch_bins: null
|
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+
train_shape_file:
|
69 |
+
- exp/tts_stats_jvs010_raw_linear_spectrogram_phn_jaconv_pyopenjtalk_prosody/train/text_shape.phn
|
70 |
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- exp/tts_stats_jvs010_raw_linear_spectrogram_phn_jaconv_pyopenjtalk_prosody/train/speech_shape
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valid_shape_file:
|
72 |
+
- exp/tts_stats_jvs010_raw_linear_spectrogram_phn_jaconv_pyopenjtalk_prosody/valid/text_shape.phn
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73 |
+
- exp/tts_stats_jvs010_raw_linear_spectrogram_phn_jaconv_pyopenjtalk_prosody/valid/speech_shape
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74 |
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batch_type: numel
|
75 |
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valid_batch_type: null
|
76 |
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fold_length:
|
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- 150
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78 |
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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
|
82 |
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chunk_length: 500
|
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chunk_shift_ratio: 0.5
|
84 |
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num_cache_chunks: 1024
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train_data_path_and_name_and_type:
|
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- - dump/22k/raw/jvs010_tr_no_dev/text
|
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- text
|
88 |
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- text
|
89 |
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- - dump/22k/raw/jvs010_tr_no_dev/wav.scp
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- speech
|
91 |
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- sound
|
92 |
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valid_data_path_and_name_and_type:
|
93 |
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- - dump/22k/raw/jvs010_dev/text
|
94 |
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- text
|
95 |
+
- text
|
96 |
+
- - dump/22k/raw/jvs010_dev/wav.scp
|
97 |
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- speech
|
98 |
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- sound
|
99 |
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allow_variable_data_keys: false
|
100 |
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max_cache_size: 0.0
|
101 |
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max_cache_fd: 32
|
102 |
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valid_max_cache_size: null
|
103 |
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optim: adamw
|
104 |
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optim_conf:
|
105 |
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lr: 0.0001
|
106 |
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betas:
|
107 |
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- 0.8
|
108 |
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- 0.99
|
109 |
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eps: 1.0e-09
|
110 |
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weight_decay: 0.0
|
111 |
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scheduler: exponentiallr
|
112 |
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scheduler_conf:
|
113 |
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gamma: 0.999875
|
114 |
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optim2: adamw
|
115 |
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optim2_conf:
|
116 |
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lr: 0.0001
|
117 |
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betas:
|
118 |
+
- 0.8
|
119 |
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- 0.99
|
120 |
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eps: 1.0e-09
|
121 |
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weight_decay: 0.0
|
122 |
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scheduler2: exponentiallr
|
123 |
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scheduler2_conf:
|
124 |
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gamma: 0.999875
|
125 |
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generator_first: false
|
126 |
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token_list:
|
127 |
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- <blank>
|
128 |
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- <unk>
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129 |
+
- a
|
130 |
+
- o
|
131 |
+
- i
|
132 |
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- '['
|
133 |
+
- '#'
|
134 |
+
- u
|
135 |
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- ']'
|
136 |
+
- e
|
137 |
+
- k
|
138 |
+
- n
|
139 |
+
- t
|
140 |
+
- r
|
141 |
+
- s
|
142 |
+
- N
|
143 |
+
- m
|
144 |
+
- _
|
145 |
+
- sh
|
146 |
+
- d
|
147 |
+
- g
|
148 |
+
- ^
|
149 |
+
- $
|
150 |
+
- w
|
151 |
+
- cl
|
152 |
+
- h
|
153 |
+
- y
|
154 |
+
- b
|
155 |
+
- j
|
156 |
+
- ts
|
157 |
+
- ch
|
158 |
+
- z
|
159 |
+
- p
|
160 |
+
- f
|
161 |
+
- ky
|
162 |
+
- ry
|
163 |
+
- gy
|
164 |
+
- hy
|
165 |
+
- ny
|
166 |
+
- by
|
167 |
+
- my
|
168 |
+
- py
|
169 |
+
- v
|
170 |
+
- dy
|
171 |
+
- '?'
|
172 |
+
- ty
|
173 |
+
- <sos/eos>
|
174 |
+
odim: null
|
175 |
+
model_conf: {}
|
176 |
+
use_preprocessor: true
|
177 |
+
token_type: phn
|
178 |
+
bpemodel: null
|
179 |
+
non_linguistic_symbols: null
|
180 |
+
cleaner: jaconv
|
181 |
+
g2p: pyopenjtalk_prosody
|
182 |
+
feats_extract: linear_spectrogram
|
183 |
+
feats_extract_conf:
|
184 |
+
n_fft: 1024
|
185 |
+
hop_length: 256
|
186 |
+
win_length: null
|
187 |
+
normalize: null
|
188 |
+
normalize_conf: {}
|
189 |
+
tts: vits
|
190 |
+
tts_conf:
|
191 |
+
generator_type: vits_generator
|
192 |
+
generator_params:
|
193 |
+
hidden_channels: 192
|
194 |
+
spks: -1
|
195 |
+
global_channels: -1
|
196 |
+
segment_size: 32
|
197 |
+
text_encoder_attention_heads: 2
|
198 |
+
text_encoder_ffn_expand: 4
|
199 |
+
text_encoder_blocks: 6
|
200 |
+
text_encoder_positionwise_layer_type: conv1d
|
201 |
+
text_encoder_positionwise_conv_kernel_size: 3
|
202 |
+
text_encoder_positional_encoding_layer_type: rel_pos
|
203 |
+
text_encoder_self_attention_layer_type: rel_selfattn
|
204 |
+
text_encoder_activation_type: swish
|
205 |
+
text_encoder_normalize_before: true
|
206 |
+
text_encoder_dropout_rate: 0.1
|
207 |
+
text_encoder_positional_dropout_rate: 0.0
|
208 |
+
text_encoder_attention_dropout_rate: 0.1
|
209 |
+
use_macaron_style_in_text_encoder: true
|
210 |
+
use_conformer_conv_in_text_encoder: false
|
211 |
+
text_encoder_conformer_kernel_size: -1
|
212 |
+
decoder_kernel_size: 7
|
213 |
+
decoder_channels: 512
|
214 |
+
decoder_upsample_scales:
|
215 |
+
- 8
|
216 |
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- 8
|
217 |
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- 2
|
218 |
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- 2
|
219 |
+
decoder_upsample_kernel_sizes:
|
220 |
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- 16
|
221 |
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- 16
|
222 |
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- 4
|
223 |
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- 4
|
224 |
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decoder_resblock_kernel_sizes:
|
225 |
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- 3
|
226 |
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- 7
|
227 |
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- 11
|
228 |
+
decoder_resblock_dilations:
|
229 |
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- - 1
|
230 |
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- 3
|
231 |
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- 5
|
232 |
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- - 1
|
233 |
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- 3
|
234 |
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- 5
|
235 |
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- - 1
|
236 |
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- 3
|
237 |
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- 5
|
238 |
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use_weight_norm_in_decoder: true
|
239 |
+
posterior_encoder_kernel_size: 5
|
240 |
+
posterior_encoder_layers: 16
|
241 |
+
posterior_encoder_stacks: 1
|
242 |
+
posterior_encoder_base_dilation: 1
|
243 |
+
posterior_encoder_dropout_rate: 0.0
|
244 |
+
use_weight_norm_in_posterior_encoder: true
|
245 |
+
flow_flows: 4
|
246 |
+
flow_kernel_size: 5
|
247 |
+
flow_base_dilation: 1
|
248 |
+
flow_layers: 4
|
249 |
+
flow_dropout_rate: 0.0
|
250 |
+
use_weight_norm_in_flow: true
|
251 |
+
use_only_mean_in_flow: true
|
252 |
+
stochastic_duration_predictor_kernel_size: 3
|
253 |
+
stochastic_duration_predictor_dropout_rate: 0.5
|
254 |
+
stochastic_duration_predictor_flows: 4
|
255 |
+
stochastic_duration_predictor_dds_conv_layers: 3
|
256 |
+
vocabs: 47
|
257 |
+
aux_channels: 513
|
258 |
+
discriminator_type: hifigan_multi_scale_multi_period_discriminator
|
259 |
+
discriminator_params:
|
260 |
+
scales: 1
|
261 |
+
scale_downsample_pooling: AvgPool1d
|
262 |
+
scale_downsample_pooling_params:
|
263 |
+
kernel_size: 4
|
264 |
+
stride: 2
|
265 |
+
padding: 2
|
266 |
+
scale_discriminator_params:
|
267 |
+
in_channels: 1
|
268 |
+
out_channels: 1
|
269 |
+
kernel_sizes:
|
270 |
+
- 15
|
271 |
+
- 41
|
272 |
+
- 5
|
273 |
+
- 3
|
274 |
+
channels: 128
|
275 |
+
max_downsample_channels: 1024
|
276 |
+
max_groups: 16
|
277 |
+
bias: true
|
278 |
+
downsample_scales:
|
279 |
+
- 2
|
280 |
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- 2
|
281 |
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- 4
|
282 |
+
- 4
|
283 |
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- 1
|
284 |
+
nonlinear_activation: LeakyReLU
|
285 |
+
nonlinear_activation_params:
|
286 |
+
negative_slope: 0.1
|
287 |
+
use_weight_norm: true
|
288 |
+
use_spectral_norm: false
|
289 |
+
follow_official_norm: false
|
290 |
+
periods:
|
291 |
+
- 2
|
292 |
+
- 3
|
293 |
+
- 5
|
294 |
+
- 7
|
295 |
+
- 11
|
296 |
+
period_discriminator_params:
|
297 |
+
in_channels: 1
|
298 |
+
out_channels: 1
|
299 |
+
kernel_sizes:
|
300 |
+
- 5
|
301 |
+
- 3
|
302 |
+
channels: 32
|
303 |
+
downsample_scales:
|
304 |
+
- 3
|
305 |
+
- 3
|
306 |
+
- 3
|
307 |
+
- 3
|
308 |
+
- 1
|
309 |
+
max_downsample_channels: 1024
|
310 |
+
bias: true
|
311 |
+
nonlinear_activation: LeakyReLU
|
312 |
+
nonlinear_activation_params:
|
313 |
+
negative_slope: 0.1
|
314 |
+
use_weight_norm: true
|
315 |
+
use_spectral_norm: false
|
316 |
+
generator_adv_loss_params:
|
317 |
+
average_by_discriminators: false
|
318 |
+
loss_type: mse
|
319 |
+
discriminator_adv_loss_params:
|
320 |
+
average_by_discriminators: false
|
321 |
+
loss_type: mse
|
322 |
+
feat_match_loss_params:
|
323 |
+
average_by_discriminators: false
|
324 |
+
average_by_layers: false
|
325 |
+
include_final_outputs: true
|
326 |
+
mel_loss_params:
|
327 |
+
fs: 22050
|
328 |
+
n_fft: 1024
|
329 |
+
hop_length: 256
|
330 |
+
win_length: null
|
331 |
+
window: hann
|
332 |
+
n_mels: 80
|
333 |
+
fmin: 0
|
334 |
+
fmax: null
|
335 |
+
log_base: null
|
336 |
+
lambda_adv: 1.0
|
337 |
+
lambda_mel: 45.0
|
338 |
+
lambda_feat_match: 2.0
|
339 |
+
lambda_dur: 1.0
|
340 |
+
lambda_kl: 1.0
|
341 |
+
sampling_rate: 22050
|
342 |
+
cache_generator_outputs: true
|
343 |
+
pitch_extract: null
|
344 |
+
pitch_extract_conf: {}
|
345 |
+
pitch_normalize: null
|
346 |
+
pitch_normalize_conf: {}
|
347 |
+
energy_extract: null
|
348 |
+
energy_extract_conf: {}
|
349 |
+
energy_normalize: null
|
350 |
+
energy_normalize_conf: {}
|
351 |
+
required:
|
352 |
+
- output_dir
|
353 |
+
- token_list
|
354 |
+
version: 0.10.3a2
|
355 |
+
distributed: true
|
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_backward_time.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_fake_loss.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_forward_time.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_loss.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_optim_step_time.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_real_loss.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/discriminator_train_time.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_adv_loss.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_backward_time.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_dur_loss.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_feat_match_loss.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_forward_time.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_kl_loss.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_loss.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_mel_loss.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_optim_step_time.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/generator_train_time.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/gpu_max_cached_mem_GB.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/iter_time.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/optim0_lr0.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/optim1_lr0.png
ADDED
exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/images/train_time.png
ADDED
meta.yaml
ADDED
@@ -0,0 +1,8 @@
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|
1 |
+
espnet: 0.10.3a2
|
2 |
+
files:
|
3 |
+
model_file: exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/100epoch.pth
|
4 |
+
python: "3.7.3 (default, Mar 27 2019, 22:11:17) \n[GCC 7.3.0]"
|
5 |
+
timestamp: 1632320193.158154
|
6 |
+
torch: 1.7.1
|
7 |
+
yaml_files:
|
8 |
+
train_config: exp/tts_finetune_jvs010_jsut_vits_raw_phn_jaconv_pyopenjtalk_prosody/config.yaml
|