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Update model

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  1. README.md +477 -0
  2. exp/22k/tts_fate_saber_vits_finetune_from_jsut/config.yaml +396 -0
  3. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/discriminator_backward_time.png +0 -0
  4. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/discriminator_fake_loss.png +0 -0
  5. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/discriminator_forward_time.png +0 -0
  6. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/discriminator_loss.png +0 -0
  7. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/discriminator_optim_step_time.png +0 -0
  8. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/discriminator_real_loss.png +0 -0
  9. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/discriminator_train_time.png +0 -0
  10. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/generator_adv_loss.png +0 -0
  11. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/generator_backward_time.png +0 -0
  12. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/generator_dur_loss.png +0 -0
  13. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/generator_feat_match_loss.png +0 -0
  14. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/generator_forward_time.png +0 -0
  15. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/generator_kl_loss.png +0 -0
  16. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/generator_loss.png +0 -0
  17. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/generator_mel_loss.png +0 -0
  18. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/generator_optim_step_time.png +0 -0
  19. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/generator_train_time.png +0 -0
  20. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/gpu_max_cached_mem_GB.png +0 -0
  21. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/iter_time.png +0 -0
  22. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/optim0_lr0.png +0 -0
  23. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/optim1_lr0.png +0 -0
  24. exp/22k/tts_fate_saber_vits_finetune_from_jsut/images/train_time.png +0 -0
  25. exp/22k/tts_fate_saber_vits_finetune_from_jsut/train.total_count.ave_10best.pth +3 -0
  26. exp/22k/tts_stats_raw_linear_spectrogram_phn_jaconv_pyopenjtalk_accent_with_pause/train/feats_stats.npz +3 -0
  27. meta.yaml +8 -0
README.md ADDED
@@ -0,0 +1,477 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - espnet
4
+ - audio
5
+ - text-to-speech
6
+ language: jp
7
+ datasets:
8
+ - fate
9
+ license: cc-by-4.0
10
+ ---
11
+
12
+ ## ESPnet2 TTS model
13
+
14
+ ### `mio/Artoria`
15
+
16
+ This model was trained by mio using fate recipe in [espnet](https://github.com/espnet/espnet/).
17
+
18
+ ### Demo: How to use in ESPnet2
19
+
20
+ Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html)
21
+ if you haven't done that already.
22
+
23
+ ```bash
24
+ cd espnet
25
+ git checkout 49d18064f22b7508ff24a7fa70c470a65f08f1be
26
+ pip install -e .
27
+ cd egs2/fate/tts1
28
+ ./run.sh --skip_data_prep false --skip_train true --download_model mio/Artoria
29
+ ```
30
+
31
+
32
+
33
+ ## TTS config
34
+
35
+ <details><summary>expand</summary>
36
+
37
+ ```
38
+ config: conf/tuning/finetune_vits.yaml
39
+ print_config: false
40
+ log_level: INFO
41
+ dry_run: false
42
+ iterator_type: sequence
43
+ output_dir: exp/22k/tts_fate_saber_vits_finetune_from_jsut
44
+ ngpu: 1
45
+ seed: 777
46
+ num_workers: 4
47
+ num_att_plot: 0
48
+ dist_backend: nccl
49
+ dist_init_method: env://
50
+ dist_world_size: 4
51
+ dist_rank: 0
52
+ local_rank: 0
53
+ dist_master_addr: localhost
54
+ dist_master_port: 46762
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+ dist_launcher: null
56
+ multiprocessing_distributed: true
57
+ unused_parameters: true
58
+ sharded_ddp: false
59
+ cudnn_enabled: true
60
+ cudnn_benchmark: false
61
+ cudnn_deterministic: false
62
+ collect_stats: false
63
+ write_collected_feats: false
64
+ max_epoch: 10
65
+ patience: null
66
+ val_scheduler_criterion:
67
+ - valid
68
+ - loss
69
+ early_stopping_criterion:
70
+ - valid
71
+ - loss
72
+ - min
73
+ best_model_criterion:
74
+ - - train
75
+ - total_count
76
+ - max
77
+ keep_nbest_models: 10
78
+ nbest_averaging_interval: 0
79
+ grad_clip: -1
80
+ grad_clip_type: 2.0
81
+ grad_noise: false
82
+ accum_grad: 1
83
+ no_forward_run: false
84
+ resume: true
85
+ train_dtype: float32
86
+ use_amp: false
87
+ log_interval: 50
88
+ use_matplotlib: true
89
+ use_tensorboard: false
90
+ create_graph_in_tensorboard: false
91
+ use_wandb: true
92
+ wandb_project: fate
93
+ wandb_id: null
94
+ wandb_entity: null
95
+ wandb_name: vits_train_saber
96
+ wandb_model_log_interval: -1
97
+ detect_anomaly: false
98
+ pretrain_path: null
99
+ init_param:
100
+ - downloads/f3698edf589206588f58f5ec837fa516/exp/tts_train_vits_raw_phn_jaconv_pyopenjtalk_accent_with_pause/train.total_count.ave_10best.pth:tts:tts
101
+ ignore_init_mismatch: false
102
+ freeze_param: []
103
+ num_iters_per_epoch: 1000
104
+ batch_size: 20
105
+ valid_batch_size: null
106
+ batch_bins: 5000000
107
+ valid_batch_bins: null
108
+ train_shape_file:
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+ - exp/22k/tts_stats_raw_linear_spectrogram_phn_jaconv_pyopenjtalk_accent_with_pause/train/text_shape.phn
110
+ - exp/22k/tts_stats_raw_linear_spectrogram_phn_jaconv_pyopenjtalk_accent_with_pause/train/speech_shape
111
+ valid_shape_file:
112
+ - exp/22k/tts_stats_raw_linear_spectrogram_phn_jaconv_pyopenjtalk_accent_with_pause/valid/text_shape.phn
113
+ - exp/22k/tts_stats_raw_linear_spectrogram_phn_jaconv_pyopenjtalk_accent_with_pause/valid/speech_shape
114
+ batch_type: numel
115
+ valid_batch_type: null
116
+ fold_length:
117
+ - 150
118
+ - 204800
119
+ sort_in_batch: descending
120
+ sort_batch: descending
121
+ multiple_iterator: false
122
+ chunk_length: 500
123
+ chunk_shift_ratio: 0.5
124
+ num_cache_chunks: 1024
125
+ train_data_path_and_name_and_type:
126
+ - - dump/22k/raw/train/text
127
+ - text
128
+ - text
129
+ - - dump/22k/raw/train/wav.scp
130
+ - speech
131
+ - sound
132
+ valid_data_path_and_name_and_type:
133
+ - - dump/22k/raw/dev/text
134
+ - text
135
+ - text
136
+ - - dump/22k/raw/dev/wav.scp
137
+ - speech
138
+ - sound
139
+ allow_variable_data_keys: false
140
+ max_cache_size: 0.0
141
+ max_cache_fd: 32
142
+ valid_max_cache_size: null
143
+ optim: adamw
144
+ optim_conf:
145
+ lr: 0.0001
146
+ betas:
147
+ - 0.8
148
+ - 0.99
149
+ eps: 1.0e-09
150
+ weight_decay: 0.0
151
+ scheduler: exponentiallr
152
+ scheduler_conf:
153
+ gamma: 0.999875
154
+ optim2: adamw
155
+ optim2_conf:
156
+ lr: 0.0001
157
+ betas:
158
+ - 0.8
159
+ - 0.99
160
+ eps: 1.0e-09
161
+ weight_decay: 0.0
162
+ scheduler2: exponentiallr
163
+ scheduler2_conf:
164
+ gamma: 0.999875
165
+ generator_first: false
166
+ token_list:
167
+ - <blank>
168
+ - <unk>
169
+ - '1'
170
+ - '2'
171
+ - '0'
172
+ - '3'
173
+ - '4'
174
+ - '-1'
175
+ - '5'
176
+ - a
177
+ - o
178
+ - '-2'
179
+ - i
180
+ - '-3'
181
+ - u
182
+ - e
183
+ - k
184
+ - n
185
+ - t
186
+ - '6'
187
+ - r
188
+ - '-4'
189
+ - s
190
+ - N
191
+ - m
192
+ - pau
193
+ - '7'
194
+ - sh
195
+ - d
196
+ - g
197
+ - w
198
+ - '8'
199
+ - U
200
+ - '-5'
201
+ - I
202
+ - cl
203
+ - h
204
+ - y
205
+ - b
206
+ - '9'
207
+ - j
208
+ - ts
209
+ - ch
210
+ - '-6'
211
+ - z
212
+ - p
213
+ - '-7'
214
+ - f
215
+ - ky
216
+ - ry
217
+ - '-8'
218
+ - gy
219
+ - '-9'
220
+ - hy
221
+ - ny
222
+ - '-10'
223
+ - by
224
+ - my
225
+ - '-11'
226
+ - '-12'
227
+ - '-13'
228
+ - py
229
+ - '-14'
230
+ - '-15'
231
+ - v
232
+ - '10'
233
+ - '-16'
234
+ - '-17'
235
+ - '11'
236
+ - '-21'
237
+ - '-20'
238
+ - '12'
239
+ - '-19'
240
+ - '13'
241
+ - '-18'
242
+ - '14'
243
+ - dy
244
+ - '15'
245
+ - ty
246
+ - '-22'
247
+ - '16'
248
+ - '18'
249
+ - '19'
250
+ - '17'
251
+ - <sos/eos>
252
+ odim: null
253
+ model_conf: {}
254
+ use_preprocessor: true
255
+ token_type: phn
256
+ bpemodel: null
257
+ non_linguistic_symbols: null
258
+ cleaner: jaconv
259
+ g2p: pyopenjtalk_accent_with_pause
260
+ feats_extract: linear_spectrogram
261
+ feats_extract_conf:
262
+ n_fft: 1024
263
+ hop_length: 256
264
+ win_length: null
265
+ normalize: null
266
+ normalize_conf: {}
267
+ tts: vits
268
+ tts_conf:
269
+ generator_type: vits_generator
270
+ generator_params:
271
+ hidden_channels: 192
272
+ spks: -1
273
+ global_channels: -1
274
+ segment_size: 32
275
+ text_encoder_attention_heads: 2
276
+ text_encoder_ffn_expand: 4
277
+ text_encoder_blocks: 6
278
+ text_encoder_positionwise_layer_type: conv1d
279
+ text_encoder_positionwise_conv_kernel_size: 3
280
+ text_encoder_positional_encoding_layer_type: rel_pos
281
+ text_encoder_self_attention_layer_type: rel_selfattn
282
+ text_encoder_activation_type: swish
283
+ text_encoder_normalize_before: true
284
+ text_encoder_dropout_rate: 0.1
285
+ text_encoder_positional_dropout_rate: 0.0
286
+ text_encoder_attention_dropout_rate: 0.1
287
+ use_macaron_style_in_text_encoder: true
288
+ use_conformer_conv_in_text_encoder: false
289
+ text_encoder_conformer_kernel_size: -1
290
+ decoder_kernel_size: 7
291
+ decoder_channels: 512
292
+ decoder_upsample_scales:
293
+ - 8
294
+ - 8
295
+ - 2
296
+ - 2
297
+ decoder_upsample_kernel_sizes:
298
+ - 16
299
+ - 16
300
+ - 4
301
+ - 4
302
+ decoder_resblock_kernel_sizes:
303
+ - 3
304
+ - 7
305
+ - 11
306
+ decoder_resblock_dilations:
307
+ - - 1
308
+ - 3
309
+ - 5
310
+ - - 1
311
+ - 3
312
+ - 5
313
+ - - 1
314
+ - 3
315
+ - 5
316
+ use_weight_norm_in_decoder: true
317
+ posterior_encoder_kernel_size: 5
318
+ posterior_encoder_layers: 16
319
+ posterior_encoder_stacks: 1
320
+ posterior_encoder_base_dilation: 1
321
+ posterior_encoder_dropout_rate: 0.0
322
+ use_weight_norm_in_posterior_encoder: true
323
+ flow_flows: 4
324
+ flow_kernel_size: 5
325
+ flow_base_dilation: 1
326
+ flow_layers: 4
327
+ flow_dropout_rate: 0.0
328
+ use_weight_norm_in_flow: true
329
+ use_only_mean_in_flow: true
330
+ stochastic_duration_predictor_kernel_size: 3
331
+ stochastic_duration_predictor_dropout_rate: 0.5
332
+ stochastic_duration_predictor_flows: 4
333
+ stochastic_duration_predictor_dds_conv_layers: 3
334
+ vocabs: 85
335
+ aux_channels: 513
336
+ discriminator_type: hifigan_multi_scale_multi_period_discriminator
337
+ discriminator_params:
338
+ scales: 1
339
+ scale_downsample_pooling: AvgPool1d
340
+ scale_downsample_pooling_params:
341
+ kernel_size: 4
342
+ stride: 2
343
+ padding: 2
344
+ scale_discriminator_params:
345
+ in_channels: 1
346
+ out_channels: 1
347
+ kernel_sizes:
348
+ - 15
349
+ - 41
350
+ - 5
351
+ - 3
352
+ channels: 128
353
+ max_downsample_channels: 1024
354
+ max_groups: 16
355
+ bias: true
356
+ downsample_scales:
357
+ - 2
358
+ - 2
359
+ - 4
360
+ - 4
361
+ - 1
362
+ nonlinear_activation: LeakyReLU
363
+ nonlinear_activation_params:
364
+ negative_slope: 0.1
365
+ use_weight_norm: true
366
+ use_spectral_norm: false
367
+ follow_official_norm: false
368
+ periods:
369
+ - 2
370
+ - 3
371
+ - 5
372
+ - 7
373
+ - 11
374
+ period_discriminator_params:
375
+ in_channels: 1
376
+ out_channels: 1
377
+ kernel_sizes:
378
+ - 5
379
+ - 3
380
+ channels: 32
381
+ downsample_scales:
382
+ - 3
383
+ - 3
384
+ - 3
385
+ - 3
386
+ - 1
387
+ max_downsample_channels: 1024
388
+ bias: true
389
+ nonlinear_activation: LeakyReLU
390
+ nonlinear_activation_params:
391
+ negative_slope: 0.1
392
+ use_weight_norm: true
393
+ use_spectral_norm: false
394
+ generator_adv_loss_params:
395
+ average_by_discriminators: false
396
+ loss_type: mse
397
+ discriminator_adv_loss_params:
398
+ average_by_discriminators: false
399
+ loss_type: mse
400
+ feat_match_loss_params:
401
+ average_by_discriminators: false
402
+ average_by_layers: false
403
+ include_final_outputs: true
404
+ mel_loss_params:
405
+ fs: 22050
406
+ n_fft: 1024
407
+ hop_length: 256
408
+ win_length: null
409
+ window: hann
410
+ n_mels: 80
411
+ fmin: 0
412
+ fmax: null
413
+ log_base: null
414
+ lambda_adv: 1.0
415
+ lambda_mel: 45.0
416
+ lambda_feat_match: 2.0
417
+ lambda_dur: 1.0
418
+ lambda_kl: 1.0
419
+ sampling_rate: 22050
420
+ cache_generator_outputs: true
421
+ pitch_extract: null
422
+ pitch_extract_conf: {}
423
+ pitch_normalize: null
424
+ pitch_normalize_conf: {}
425
+ energy_extract: null
426
+ energy_extract_conf: {}
427
+ energy_normalize: null
428
+ energy_normalize_conf: {}
429
+ required:
430
+ - output_dir
431
+ - token_list
432
+ version: '202207'
433
+ distributed: true
434
+ ```
435
+
436
+ </details>
437
+
438
+
439
+
440
+ ### Citing ESPnet
441
+
442
+ ```BibTex
443
+ @inproceedings{watanabe2018espnet,
444
+ 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},
445
+ title={{ESPnet}: End-to-End Speech Processing Toolkit},
446
+ year={2018},
447
+ booktitle={Proceedings of Interspeech},
448
+ pages={2207--2211},
449
+ doi={10.21437/Interspeech.2018-1456},
450
+ url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
451
+ }
452
+
453
+
454
+
455
+
456
+ @inproceedings{hayashi2020espnet,
457
+ title={{Espnet-TTS}: Unified, reproducible, and integratable open source end-to-end text-to-speech toolkit},
458
+ 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},
459
+ booktitle={Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
460
+ pages={7654--7658},
461
+ year={2020},
462
+ organization={IEEE}
463
+ }
464
+ ```
465
+
466
+ or arXiv:
467
+
468
+ ```bibtex
469
+ @misc{watanabe2018espnet,
470
+ title={ESPnet: End-to-End Speech Processing Toolkit},
471
+ 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},
472
+ year={2018},
473
+ eprint={1804.00015},
474
+ archivePrefix={arXiv},
475
+ primaryClass={cs.CL}
476
+ }
477
+ ```
exp/22k/tts_fate_saber_vits_finetune_from_jsut/config.yaml ADDED
@@ -0,0 +1,396 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ config: conf/tuning/finetune_vits.yaml
2
+ print_config: false
3
+ log_level: INFO
4
+ dry_run: false
5
+ iterator_type: sequence
6
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