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config update for ljspeech

This commit is contained in:
Eren Golge 2019-04-08 16:45:50 +02:00
parent 5afd3d980b
commit 303dc9d62e
1 changed files with 9 additions and 9 deletions
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config.json
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@ -1,6 +1,6 @@
{
"run_name": "bos",
"run_description": "finetune entropy model due to some spelling mistakes.",
"run_name": "ljspeech",
"run_description": "finetune 4241 for align with architectural changes",
"audio":{
// Audio processing parameters
@ -40,10 +40,10 @@
"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": "softmax", // softmax or sigmoid. Suggested to use softmax for Tacotron2 and sigmoid for Tacotron.
"prenet_type": "original", // ONLY TACOTRON2 - "original" or "bn".
"prenet_type": "bn", // ONLY TACOTRON2 - "original" or "bn".
"use_forward_attn": false, // ONLY TACOTRON2 - if it uses forward attention. In general, it aligns faster.
"batch_size": 32, // Batch size for training. Lower values than 32 might cause hard to learn attention.
"batch_size": 16, // Batch size for training. Lower values than 32 might cause hard to learn attention.
"eval_batch_size":16,
"r": 1, // Number of frames to predict for step.
"wd": 0.000001, // Weight decay weight.
@ -55,16 +55,16 @@
"run_eval": true,
"test_delay_epochs": 2, //Until attention is aligned, testing only wastes computation time.
"data_path": "/media/erogol/data_ssd/Data/Nancy/", // DATASET-RELATED: can overwritten from command argument
"meta_file_train": "prompts_train.data", // DATASET-RELATED: metafile for training dataloader.
"meta_file_val": "prompts_val.data", // DATASET-RELATED: metafile for evaluation dataloader.
"dataset": "nancy", // DATASET-RELATED: one of TTS.dataset.preprocessors depending on your target dataset. Use "tts_cache" for pre-computed dataset by extract_features.py
"data_path": "/home/erogol/Data/LJSpeech-1.1", // DATASET-RELATED: can overwritten from command argument
"meta_file_train": "metadata_train.csv", // DATASET-RELATED: metafile for training dataloader.
"meta_file_val": "metadata_val.csv", // DATASET-RELATED: metafile for evaluation dataloader.
"dataset": "ljspeech", // 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": 0, // DATASET-RELATED: minimum text length to use in training
"max_seq_len": 150, // DATASET-RELATED: maximum text length
"output_path": "/media/erogol/data_ssd/Data/models/ljspeech_models/", // DATASET-RELATED: output path for all training outputs.
"num_loader_workers": 8, // 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": "nancy_us_phonemes2", // phoneme computation is slow, therefore, it caches results in the given folder.
"phoneme_cache_path": "ljspeech_phonemes", // 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": "en-us", // depending on your target language, pick one from https://github.com/bootphon/phonemizer#languages
"text_cleaner": "phoneme_cleaners"