mirror of https://github.com/coqui-ai/TTS.git
config update for nancy
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.compute
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.compute
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@ -3,5 +3,5 @@ ls ${SHARED_DIR}/data/
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pip3 install https://download.pytorch.org/whl/cu100/torch-1.0.1.post2-cp36-cp36m-linux_x86_64.whl
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yes | apt-get install espeak
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python3 setup.py develop
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# python3 distribute.py --config_path config_cluster.json --data_path ${SHARED_DIR}/data/keithito/LJSpeech-1.1/ --restore_path ${USER_DIR}/best_model.pth.tar
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python3 distribute.py --config_path config_cluster.json --data_path ${SHARED_DIR}/data/Blizzard/Nancy/
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python3 distribute.py --config_path config_cluster.json --data_path ${SHARED_DIR}/data/Blizzard/Nancy/ --restore_path ${USER_DIR}/best_model.pth.tar
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# python3 distribute.py --config_path config_cluster.json --data_path ${SHARED_DIR}/data/Blizzard/Nancy/
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@ -6,7 +6,7 @@
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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": 22050, // wav sample-rate. If different than the original data, it is resampled.
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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.
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"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.
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@ -21,7 +21,7 @@
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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": false // enable trimming of slience of audio as you load it. LJspeech (false), TWEB (false), Nancy (true)
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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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