TTS/config_tacotron_de.json

{
            "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. 
            
            "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"
        }