import from zenodo
Browse files- README.md +50 -0
- exp/tts_stats_raw_phn_jaconv_pyopenjtalk_prosody/train/feats_stats.npz +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/config.yaml +225 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/attn_loss.png +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/backward_time.png +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/bce_loss.png +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/forward_time.png +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/gpu_max_cached_mem_GB.png +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/iter_time.png +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/l1_loss.png +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/loss.png +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/mse_loss.png +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/optim0_lr0.png +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/optim_step_time.png +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/train_time.png +0 -0
- exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/train.loss.ave_5best.pth +3 -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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- jsut
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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/jsut_tacotron2_prosody`
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♻️ Imported from https://zenodo.org/record/5499026/
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This model was trained by kan-bayashi using jsut/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_stats_raw_phn_jaconv_pyopenjtalk_prosody/train/feats_stats.npz
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Binary file (1.4 kB). View file
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exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/config.yaml
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config: conf/tuning/train_tacotron2.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_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody
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ngpu: 1
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seed: 0
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num_workers: 1
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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: null
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dist_rank: null
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local_rank: 0
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dist_master_addr: null
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dist_master_port: null
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dist_launcher: null
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multiprocessing_distributed: false
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unused_parameters: false
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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: true
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collect_stats: false
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26 |
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write_collected_feats: false
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27 |
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max_epoch: 200
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patience: null
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29 |
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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
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34 |
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- loss
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35 |
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- min
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36 |
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best_model_criterion:
|
37 |
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- - valid
|
38 |
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- loss
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39 |
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- min
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40 |
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- - train
|
41 |
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- loss
|
42 |
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- min
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43 |
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keep_nbest_models: 5
|
44 |
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grad_clip: 1.0
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45 |
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grad_clip_type: 2.0
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grad_noise: false
|
47 |
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accum_grad: 1
|
48 |
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no_forward_run: false
|
49 |
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resume: true
|
50 |
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train_dtype: float32
|
51 |
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use_amp: false
|
52 |
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log_interval: null
|
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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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56 |
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wandb_id: null
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wandb_entity: null
|
58 |
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wandb_name: null
|
59 |
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wandb_model_log_interval: -1
|
60 |
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detect_anomaly: false
|
61 |
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pretrain_path: null
|
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init_param: []
|
63 |
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ignore_init_mismatch: false
|
64 |
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freeze_param: []
|
65 |
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num_iters_per_epoch: 500
|
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batch_size: 20
|
67 |
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valid_batch_size: null
|
68 |
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batch_bins: 3750000
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valid_batch_bins: null
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train_shape_file:
|
71 |
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- exp/tts_stats_raw_phn_jaconv_pyopenjtalk_prosody/train/text_shape.phn
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- exp/tts_stats_raw_phn_jaconv_pyopenjtalk_prosody/train/speech_shape
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73 |
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valid_shape_file:
|
74 |
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- exp/tts_stats_raw_phn_jaconv_pyopenjtalk_prosody/valid/text_shape.phn
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75 |
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- exp/tts_stats_raw_phn_jaconv_pyopenjtalk_prosody/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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- 240000
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sort_in_batch: descending
|
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sort_batch: descending
|
83 |
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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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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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valid_data_path_and_name_and_type:
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- - dump/raw/dev/text
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- text
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97 |
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- text
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98 |
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- - dump/raw/dev/wav.scp
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- speech
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- sound
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101 |
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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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optim: adam
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optim_conf:
|
107 |
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lr: 0.001
|
108 |
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eps: 1.0e-06
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weight_decay: 0.0
|
110 |
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scheduler: null
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scheduler_conf: {}
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token_list:
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- <blank>
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- <unk>
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- a
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- o
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117 |
+
- i
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118 |
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- '['
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119 |
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- '#'
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120 |
+
- u
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- ']'
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122 |
+
- e
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123 |
+
- k
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124 |
+
- n
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+
- t
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126 |
+
- r
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127 |
+
- s
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128 |
+
- N
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129 |
+
- m
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130 |
+
- _
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131 |
+
- sh
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132 |
+
- d
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133 |
+
- g
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+
- ^
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135 |
+
- $
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136 |
+
- w
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137 |
+
- cl
|
138 |
+
- h
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139 |
+
- y
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140 |
+
- b
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141 |
+
- j
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+
- ts
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+
- ch
|
144 |
+
- z
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145 |
+
- p
|
146 |
+
- f
|
147 |
+
- ky
|
148 |
+
- ry
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149 |
+
- gy
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150 |
+
- hy
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151 |
+
- ny
|
152 |
+
- by
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153 |
+
- my
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154 |
+
- py
|
155 |
+
- v
|
156 |
+
- dy
|
157 |
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- '?'
|
158 |
+
- ty
|
159 |
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- <sos/eos>
|
160 |
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odim: null
|
161 |
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model_conf: {}
|
162 |
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use_preprocessor: true
|
163 |
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token_type: phn
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164 |
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bpemodel: null
|
165 |
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non_linguistic_symbols: null
|
166 |
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cleaner: jaconv
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167 |
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g2p: pyopenjtalk_prosody
|
168 |
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feats_extract: fbank
|
169 |
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feats_extract_conf:
|
170 |
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n_fft: 2048
|
171 |
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hop_length: 300
|
172 |
+
win_length: 1200
|
173 |
+
fs: 24000
|
174 |
+
fmin: 80
|
175 |
+
fmax: 7600
|
176 |
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n_mels: 80
|
177 |
+
normalize: global_mvn
|
178 |
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normalize_conf:
|
179 |
+
stats_file: exp/tts_stats_raw_phn_jaconv_pyopenjtalk_prosody/train/feats_stats.npz
|
180 |
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tts: tacotron2
|
181 |
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tts_conf:
|
182 |
+
embed_dim: 512
|
183 |
+
elayers: 1
|
184 |
+
eunits: 512
|
185 |
+
econv_layers: 3
|
186 |
+
econv_chans: 512
|
187 |
+
econv_filts: 5
|
188 |
+
atype: location
|
189 |
+
adim: 512
|
190 |
+
aconv_chans: 32
|
191 |
+
aconv_filts: 15
|
192 |
+
cumulate_att_w: true
|
193 |
+
dlayers: 2
|
194 |
+
dunits: 1024
|
195 |
+
prenet_layers: 2
|
196 |
+
prenet_units: 256
|
197 |
+
postnet_layers: 5
|
198 |
+
postnet_chans: 512
|
199 |
+
postnet_filts: 5
|
200 |
+
output_activation: null
|
201 |
+
use_batch_norm: true
|
202 |
+
use_concate: true
|
203 |
+
use_residual: false
|
204 |
+
dropout_rate: 0.5
|
205 |
+
zoneout_rate: 0.1
|
206 |
+
reduction_factor: 1
|
207 |
+
spk_embed_dim: null
|
208 |
+
use_masking: true
|
209 |
+
bce_pos_weight: 5.0
|
210 |
+
use_guided_attn_loss: true
|
211 |
+
guided_attn_loss_sigma: 0.4
|
212 |
+
guided_attn_loss_lambda: 1.0
|
213 |
+
pitch_extract: null
|
214 |
+
pitch_extract_conf: {}
|
215 |
+
pitch_normalize: null
|
216 |
+
pitch_normalize_conf: {}
|
217 |
+
energy_extract: null
|
218 |
+
energy_extract_conf: {}
|
219 |
+
energy_normalize: null
|
220 |
+
energy_normalize_conf: {}
|
221 |
+
required:
|
222 |
+
- output_dir
|
223 |
+
- token_list
|
224 |
+
version: 0.10.3a1
|
225 |
+
distributed: false
|
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/attn_loss.png
ADDED
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/backward_time.png
ADDED
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/bce_loss.png
ADDED
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/forward_time.png
ADDED
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/gpu_max_cached_mem_GB.png
ADDED
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/iter_time.png
ADDED
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/l1_loss.png
ADDED
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/loss.png
ADDED
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/mse_loss.png
ADDED
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/optim0_lr0.png
ADDED
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/optim_step_time.png
ADDED
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/images/train_time.png
ADDED
exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/train.loss.ave_5best.pth
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:a6e912d7489e27dae8d538b4d10a8eac49191b2763ef6affb0b2da9c8b2559ce
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size 106960730
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meta.yaml
ADDED
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espnet: 0.10.3a2
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files:
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model_file: exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/train.loss.ave_5best.pth
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python: "3.7.3 (default, Mar 27 2019, 22:11:17) \n[GCC 7.3.0]"
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timestamp: 1631246359.054751
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torch: 1.7.1
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yaml_files:
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train_config: exp/tts_train_tacotron2_raw_phn_jaconv_pyopenjtalk_prosody/config.yaml
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