mirror of https://github.com/coqui-ai/TTS.git
config update for mean-var scaling
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erogol
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069c8e4315
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60
config.json
60
config.json
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{
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"model": "Tacotron2", // one of the model in models/
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"model": "Tacotron2",
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"run_name": "ljspeech",
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"run_description": "tacotron2 with guided attention and -1 1 normalization and no preemphasis",
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// AUDIO PARAMETERS
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"audio":{
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// stft parameters
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"num_freq": 513, // number of stft frequency levels. Size of the linear spectogram frame.
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"win_length": 1024, // stft window length in ms.
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"hop_length": 256, // stft window hop-lengh in ms.
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"frame_length_ms": null, // stft window length in ms.If null, 'win_length' is used.
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"frame_shift_ms": null, // stft window hop-lengh in ms. If null, 'hop_length' is used.
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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": 513, // number of stft frequency levels. Size of the linear spectogram frame.
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"sample_rate": 22050, // DATASET-RELATED: wav sample-rate. If different than the original data, it is resampled.
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"win_length": 1024, // stft window length in ms.
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"hop_length": 256, // stft window hop-lengh in ms.
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"preemphasis": 0.0, // pre-emphasis to reduce spec noise and make it more structured. If 0.0, no -pre-emphasis.
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"frame_length_ms": null, // stft window length in ms.If null, 'win_length' is used.
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"frame_shift_ms": null, // stft window hop-lengh in ms. If null, 'hop_length' is used.
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"min_level_db": -100, // normalization range
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"preemphasis": 0.0, // pre-emphasis to reduce spec noise and make it more structured. If 0.0, no -pre-emphasis.
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"ref_level_db": 20, // reference level db, theoretically 20db is the sound of air.
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// Silence trimming
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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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"trim_db": 60, // threshold for timming silence. Set this according to your dataset.
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// Griffin-Lim
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"power": 1.5, // value to sharpen wav signals after GL algorithm.
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"griffin_lim_iters": 60,// #griffin-lim iterations. 30-60 is a good range. Larger the value, slower the generation.
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// MelSpectrogram parameters
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"num_mels": 80, // size of the mel spec frame.
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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!!
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"mel_fmax": 8000.0, // maximum freq level for mel-spec. Tune for dataset!!
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// Normalization parameters
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"signal_norm": true, // normalize the spec values in range [0, 1]
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"signal_norm": true, // normalize spec values. Mean-Var normalization if 'stats_path' is defined otherwise range normalization defined by the other params.
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"min_level_db": -100, // lower bound for normalization
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"symmetric_norm": true, // move normalization to range [-1, 1]
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"max_norm": 1.0, // scale normalization to range [-max_norm, max_norm] or [0, max_norm]
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"max_norm": 1.0, // scale normalization to range [-max_norm, max_norm] or [0, max_norm]
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"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!!
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"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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"trim_db": 60 // threshold for timming silence. Set this according to your dataset.
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"stats_path": "/home/erogol/Data/LJSpeech-1.1/scale_stats.npy" // DO NOT USE WITH MULTI_SPEAKER MODEL. scaler stats file computed by 'compute_statistics.py'. If it is defined, mean-std based notmalization is used and other normalization params are ignored
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},
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// VOCABULARY PARAMETERS
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// if custom character set is not defined,
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// default set in symbols.py is used
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"characters":{
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"pad": "_",
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"eos": "~",
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"bos": "^",
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"characters": "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz!'(),-.:;? ",
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"punctuations":"!'(),-.:;? ",
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"phonemes":"iyɨʉɯuɪʏʊeøɘəɵɤoɛœɜɞʌɔæɐaɶɑɒᵻʘɓǀɗǃʄǂɠǁʛpbtdʈɖcɟkɡqɢʔɴŋɲɳnɱmʙrʀⱱɾɽɸβfvθðszʃʒʂʐçʝxɣχʁħʕhɦɬɮʋɹɻjɰlɭʎʟˈˌːˑʍwɥʜʢʡɕʑɺɧɚ˞ɫ"
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},
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// "characters":{
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// "pad": "_",
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// "eos": "~",
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// "bos": "^",
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// "characters": "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz!'(),-.:;? ",
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// "punctuations":"!'(),-.:;? ",
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// "phonemes":"iyɨʉɯuɪʏʊeøɘəɵɤoɛœɜɞʌɔæɐaɶɑɒᵻʘɓǀɗǃʄǂɠǁʛpbtdʈɖcɟkɡqɢʔɴŋɲɳnɱmʙrʀⱱɾɽɸβfvθðszʃʒʂʐçʝxɣχʁħʕhɦɬɮʋɹɻjɰlɭʎʟˈˌːˑʍwɥʜʢʡɕʑɺɧɚ˞ɫ"
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// },
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// DISTRIBUTED TRAINING
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"distributed":{
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@ -107,7 +117,7 @@
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"max_seq_len": 153, // DATASET-RELATED: maximum text length
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// PATHS
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"output_path": "/data4/rw/home/Trainings/",
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"output_path": "/home/erogol/Models/LJSpeech/",
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// PHONEMES
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"phoneme_cache_path": "mozilla_us_phonemes_3", // phoneme computation is slow, therefore, it caches results in the given folder.
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@ -124,7 +134,7 @@
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[
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{
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"name": "ljspeech",
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"path": "/root/LJSpeech-1.1/",
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"path": "/home/erogol/Data/LJSpeech-1.1/",
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"meta_file_train": "metadata.csv",
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"meta_file_val": null
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}
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