зеркало из https://github.com/mozilla/TTS.git
config update
This commit is contained in:
Eren Golge
Родитель
d64c4bb35b
Коммит
b35b6e8e98
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@ -1,116 +1,117 @@
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{
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"run_name": "german-tacotron-gst-softmax-loc_attn",
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"run_description": "train german with all of the german dataset",
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"audio":{
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// Audio processing parameters
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"num_mels": 80, // size of the mel spec frame.
|
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"num_freq": 1025, // number of stft frequency levels. Size of the linear spectogram frame.
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"sample_rate": 16000, // DATASET-RELATED: wav sample-rate. If different than the original data, it is resampled.
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"frame_length_ms": 50, // stft window length in ms.
|
||||
"frame_shift_ms": 12.5, // stft window hop-lengh in ms.
|
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"preemphasis": 0.98, // pre-emphasis to reduce spec noise and make it more structured. If 0.0, no -pre-emphasis.
|
||||
"min_level_db": -100, // normalization range
|
||||
"ref_level_db": 20, // reference level db, theoretically 20db is the sound of air.
|
||||
"power": 1.5, // value to sharpen wav signals after GL algorithm.
|
||||
"griffin_lim_iters": 60,// #griffin-lim iterations. 30-60 is a good range. Larger the value, slower the generation.
|
||||
// Normalization parameters
|
||||
"signal_norm": true, // normalize the spec values in range [0, 1]
|
||||
"symmetric_norm": false, // move normalization to range [-1, 1]
|
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"max_norm": 1, // scale normalization to range [-max_norm, max_norm] or [0, max_norm]
|
||||
"clip_norm": true, // clip normalized values into the range.
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"mel_fmin": 0.0, // minimum freq level for mel-spec. ~50 for male and ~95 for female voices. Tune for dataset!!
|
||||
"mel_fmax": 8000.0, // maximum freq level for mel-spec. Tune for dataset!!
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"do_trim_silence": true // enable trimming of slience of audio as you load it. LJspeech (false), TWEB (false), Nancy (true)
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},
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"distributed":{
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"backend": "nccl",
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"url": "tcp:\/\/localhost:54321"
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},
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"reinit_layers": [],
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"model": "Tacotron", // one of the model in models/
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"grad_clip": 1, // upper limit for gradients for clipping.
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"epochs": 10000, // total number of epochs to train.
|
||||
"lr": 0.0001, // Initial learning rate. If Noam decay is active, maximum learning rate.
|
||||
"lr_decay": false, // if true, Noam learning rate decaying is applied through training.
|
||||
"warmup_steps": 4000, // Noam decay steps to increase the learning rate from 0 to "lr"
|
||||
"windowing": false, // Enables attention windowing. Used only in eval mode.
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"memory_size": 5, // ONLY TACOTRON - memory queue size used to queue network predictions to feed autoregressive connection. Useful if r < 5.
|
||||
"attention_norm": "sigmoid", // softmax or sigmoid. Suggested to use softmax for Tacotron2 and sigmoid for Tacotron.
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"prenet_type": "original", // ONLY TACOTRON2 - "original" or "bn".
|
||||
"prenet_dropout": true, // ONLY TACOTRON2 - enable/disable dropout at prenet.
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"use_forward_attn": true, // ONLY TACOTRON2 - if it uses forward attention. In general, it aligns faster.
|
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"transition_agent": false, // ONLY TACOTRON2 - enable/disable transition agent of forward attention.
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"forward_attn_mask": true,
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"location_attn": true, // ONLY TACOTRON2 - enable_disable location sensitive attention. It is enabled for TACOTRON by default.
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"loss_masking": true, // enable / disable loss masking against the sequence padding.
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"enable_eos_bos_chars": false, // enable/disable beginning of sentence and end of sentence chars.
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"stopnet": true, // Train stopnet predicting the end of synthesis.
|
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"separate_stopnet": true, // Train stopnet seperately if 'stopnet==true'. It prevents stopnet loss to influence the rest of the model. It causes a better model, but it trains SLOWER.
|
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"tb_model_param_stats": false, // true, plots param stats per layer on tensorboard. Might be memory consuming, but good for debugging.
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"github_branch":"tacotron-gst",
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"run_name": "german-karlsson-tacotron-loc_attn",
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"run_description": "train german with all of the german dataset",
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"batch_size": 32, // Batch size for training. Lower values than 32 might cause hard to learn attention.
|
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"eval_batch_size":32,
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"r": 5, // Number of frames to predict for step.
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"wd": 0.000001, // Weight decay weight.
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"checkpoint": true, // If true, it saves checkpoints per "save_step"
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"save_step": 1000, // Number of training steps expected to save traning stats and checkpoints.
|
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"print_step": 10, // Number of steps to log traning on console.
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"batch_group_size": 0, //Number of batches to shuffle after bucketing.
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"run_eval": false,
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"test_sentences_file": "de_sentences.txt", // set a file to load sentences to be used for testing. If it is null then we use default english sentences.
|
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"test_delay_epochs": 5, //Until attention is aligned, testing only wastes computation time.
|
||||
"data_path": "/home/erogol/Data/m-ai-labs/de_DE/by_book/" , // DATASET-RELATED: can overwritten from command argument
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||||
"meta_file_train": [
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||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/mix/erzaehlungen_poe/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/mix/auf_zwei_planeten/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/kleinzaches/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/spiegel_kaetzchen/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/herrnarnesschatz/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/maedchen_von_moorhof/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/koenigsgaukler/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/altehous/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/odysseus/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/undine/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/reise_tilsit/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/schmied_seines_glueckes/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/kammmacher/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/unterm_birnbaum/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/liebesbriefe/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/sandmann/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/eva_k/kleine_lord/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/eva_k/toten_seelen/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/eva_k/werde_die_du_bist/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/eva_k/grune_haus/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/rebecca_braunert_plunkett/das_letzte_marchen/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/rebecca_braunert_plunkett/ferien_vom_ich/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/rebecca_braunert_plunkett/maerchen/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/rebecca_braunert_plunkett/mein_weg_als_deutscher_und_jude/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/caspar/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/sterben/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/weihnachtsabend/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/frankenstein/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/tschun/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/menschenhasser/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/grune_gesicht/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/tom_sawyer/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/alter_afrikaner/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/female/angela_merkel/merkel_alone/metadata.csv"
|
||||
], // DATASET-RELATED: metafile for training dataloader.
|
||||
"meta_file_val": null, // DATASET-RELATED: metafile for evaluation dataloader.
|
||||
"dataset": "mailabs", // DATASET-RELATED: one of TTS.dataset.preprocessors depending on your target dataset. Use "tts_cache" for pre-computed dataset by extract_features.py
|
||||
"min_seq_len": 15, // DATASET-RELATED: minimum text length to use in training
|
||||
"max_seq_len": 200, // DATASET-RELATED: maximum text length
|
||||
"output_path": "/media/erogol/data_ssd/Data/models/mozilla_models/", // DATASET-RELATED: output path for all training outputs.
|
||||
"num_loader_workers": 0, // number of training data loader processes. Don't set it too big. 4-8 are good values.
|
||||
"num_val_loader_workers": 4, // number of evaluation data loader processes.
|
||||
"phoneme_cache_path": "phoneme_cache", // phoneme computation is slow, therefore, it caches results in the given folder.
|
||||
"use_phonemes": true, // use phonemes instead of raw characters. It is suggested for better pronounciation.
|
||||
"phoneme_language": "de", // depending on your target language, pick one from https://github.com/bootphon/phonemizer#languages
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"text_cleaner": "phoneme_cleaners"
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}
|
||||
|
||||
"audio":{
|
||||
// Audio processing parameters
|
||||
"num_mels": 80, // size of the mel spec frame.
|
||||
"num_freq": 1025, // number of stft frequency levels. Size of the linear spectogram frame.
|
||||
"sample_rate": 16000, // DATASET-RELATED: wav sample-rate. If different than the original data, it is resampled.
|
||||
"frame_length_ms": 50, // stft window length in ms.
|
||||
"frame_shift_ms": 12.5, // stft window hop-lengh in ms.
|
||||
"preemphasis": 0.98, // pre-emphasis to reduce spec noise and make it more structured. If 0.0, no -pre-emphasis.
|
||||
"min_level_db": -100, // normalization range
|
||||
"ref_level_db": 20, // reference level db, theoretically 20db is the sound of air.
|
||||
"power": 1.5, // value to sharpen wav signals after GL algorithm.
|
||||
"griffin_lim_iters": 60,// #griffin-lim iterations. 30-60 is a good range. Larger the value, slower the generation.
|
||||
// Normalization parameters
|
||||
"signal_norm": true, // normalize the spec values in range [0, 1]
|
||||
"symmetric_norm": false, // move normalization to range [-1, 1]
|
||||
"max_norm": 1, // scale normalization to range [-max_norm, max_norm] or [0, max_norm]
|
||||
"clip_norm": true, // clip normalized values into the range.
|
||||
"mel_fmin": 0.0, // minimum freq level for mel-spec. ~50 for male and ~95 for female voices. Tune for dataset!!
|
||||
"mel_fmax": 8000.0, // maximum freq level for mel-spec. Tune for dataset!!
|
||||
"do_trim_silence": true // enable trimming of slience of audio as you load it. LJspeech (false), TWEB (false), Nancy (true)
|
||||
},
|
||||
|
||||
"distributed":{
|
||||
"backend": "nccl",
|
||||
"url": "tcp:\/\/localhost:54321"
|
||||
},
|
||||
|
||||
"reinit_layers": [],
|
||||
|
||||
"model": "Tacotron", // one of the model in models/
|
||||
"grad_clip": 1, // upper limit for gradients for clipping.
|
||||
"epochs": 10000, // total number of epochs to train.
|
||||
"lr": 0.0001, // Initial learning rate. If Noam decay is active, maximum learning rate.
|
||||
"lr_decay": false, // if true, Noam learning rate decaying is applied through training.
|
||||
"warmup_steps": 4000, // Noam decay steps to increase the learning rate from 0 to "lr"
|
||||
"windowing": false, // Enables attention windowing. Used only in eval mode.
|
||||
"memory_size": 5, // ONLY TACOTRON - memory queue size used to queue network predictions to feed autoregressive connection. Useful if r < 5.
|
||||
"attention_norm": "sigmoid", // softmax or sigmoid. Suggested to use softmax for Tacotron2 and sigmoid for Tacotron.
|
||||
"prenet_type": "original", // ONLY TACOTRON2 - "original" or "bn".
|
||||
"prenet_dropout": true, // ONLY TACOTRON2 - enable/disable dropout at prenet.
|
||||
"use_forward_attn": true, // ONLY TACOTRON2 - if it uses forward attention. In general, it aligns faster.
|
||||
"transition_agent": false, // ONLY TACOTRON2 - enable/disable transition agent of forward attention.
|
||||
"forward_attn_mask": true,
|
||||
"location_attn": true, // ONLY TACOTRON2 - enable_disable location sensitive attention. It is enabled for TACOTRON by default.
|
||||
"loss_masking": true, // enable / disable loss masking against the sequence padding.
|
||||
"enable_eos_bos_chars": false, // enable/disable beginning of sentence and end of sentence chars.
|
||||
"stopnet": true, // Train stopnet predicting the end of synthesis.
|
||||
"separate_stopnet": true, // Train stopnet seperately if 'stopnet==true'. It prevents stopnet loss to influence the rest of the model. It causes a better model, but it trains SLOWER.
|
||||
"tb_model_param_stats": false, // true, plots param stats per layer on tensorboard. Might be memory consuming, but good for debugging.
|
||||
|
||||
"batch_size": 32, // Batch size for training. Lower values than 32 might cause hard to learn attention.
|
||||
"eval_batch_size":32,
|
||||
"r": 5, // Number of frames to predict for step.
|
||||
"wd": 0.000001, // Weight decay weight.
|
||||
"checkpoint": true, // If true, it saves checkpoints per "save_step"
|
||||
"save_step": 1000, // Number of training steps expected to save traning stats and checkpoints.
|
||||
"print_step": 10, // Number of steps to log traning on console.
|
||||
"batch_group_size": 0, //Number of batches to shuffle after bucketing.
|
||||
|
||||
"run_eval": false,
|
||||
"test_sentences_file": "de_sentences.txt", // set a file to load sentences to be used for testing. If it is null then we use default english sentences.
|
||||
"test_delay_epochs": 5, //Until attention is aligned, testing only wastes computation time.
|
||||
"data_path": "/home/erogol/Data/m-ai-labs/de_DE/by_book/" , // DATASET-RELATED: can overwritten from command argument
|
||||
"meta_file_train": [
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/mix/erzaehlungen_poe/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/mix/auf_zwei_planeten/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/kleinzaches/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/spiegel_kaetzchen/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/herrnarnesschatz/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/maedchen_von_moorhof/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/koenigsgaukler/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/altehous/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/odysseus/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/undine/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/reise_tilsit/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/schmied_seines_glueckes/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/kammmacher/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/unterm_birnbaum/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/liebesbriefe/metadata.csv",
|
||||
"/home/erogol/Data/m-ai-labs/de_DE/by_book/male/karlsson/sandmann/metadata.csv"
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/eva_k/kleine_lord/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/eva_k/toten_seelen/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/eva_k/werde_die_du_bist/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/eva_k/grune_haus/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/rebecca_braunert_plunkett/das_letzte_marchen/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/rebecca_braunert_plunkett/ferien_vom_ich/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/rebecca_braunert_plunkett/maerchen/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/rebecca_braunert_plunkett/mein_weg_als_deutscher_und_jude/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/caspar/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/sterben/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/weihnachtsabend/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/frankenstein/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/tschun/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/menschenhasser/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/grune_gesicht/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/tom_sawyer/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/ramona_deininger/alter_afrikaner/metadata.csv",
|
||||
// "/home/erogol/Data/m-ai-labs/de_DE/by_book/female/angela_merkel/merkel_alone/metadata.csv"
|
||||
], // DATASET-RELATED: metafile for training dataloader.
|
||||
"meta_file_val": null, // DATASET-RELATED: metafile for evaluation dataloader.
|
||||
"dataset": "mailabs", // DATASET-RELATED: one of TTS.dataset.preprocessors depending on your target dataset. Use "tts_cache" for pre-computed dataset by extract_features.py
|
||||
"min_seq_len": 15, // DATASET-RELATED: minimum text length to use in training
|
||||
"max_seq_len": 200, // DATASET-RELATED: maximum text length
|
||||
"output_path": "/media/erogol/data_ssd/Data/models/mozilla_models/", // DATASET-RELATED: output path for all training outputs.
|
||||
"num_loader_workers": 4, // number of training data loader processes. Don't set it too big. 4-8 are good values.
|
||||
"num_val_loader_workers": 4, // number of evaluation data loader processes.
|
||||
"phoneme_cache_path": "phoneme_cache", // phoneme computation is slow, therefore, it caches results in the given folder.
|
||||
"use_phonemes": true, // use phonemes instead of raw characters. It is suggested for better pronounciation.
|
||||
"phoneme_language": "de", // depending on your target language, pick one from https://github.com/bootphon/phonemizer#languages
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"text_cleaner": "phoneme_cleaners"
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}
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Загрузка…
Ссылка в новой задаче