From b35b6e8e98ac2ab21f29984b13271c5f71d24565 Mon Sep 17 00:00:00 2001 From: Eren Golge Date: Wed, 19 Jun 2019 12:29:10 +0200 Subject: [PATCH] config update --- config_tacotron_de.json | 229 ++++++++++++++++++++-------------------- 1 file changed, 115 insertions(+), 114 deletions(-) diff --git a/config_tacotron_de.json b/config_tacotron_de.json index d60bbf58..3e5837c2 100644 --- a/config_tacotron_de.json +++ b/config_tacotron_de.json @@ -1,116 +1,117 @@ { - "run_name": "german-tacotron-gst-softmax-loc_attn", - "run_description": "train german with all of the german dataset", - - "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. + "github_branch":"tacotron-gst", + "run_name": "german-karlsson-tacotron-loc_attn", + "run_description": "train german with all of the german dataset", - "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": 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 - "text_cleaner": "phoneme_cleaners" - } - \ No newline at end of file + "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 + "text_cleaner": "phoneme_cleaners" + } + \ No newline at end of file