mirror of https://github.com/coqui-ai/TTS.git
config for tacotron2
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.compute
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.compute
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@ -11,8 +11,9 @@ sudo sh install.sh
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python3 setup.py develop
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# cp -R ${USER_DIR}/GermanData ../tmp/
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# cp -R /data/ro/shared/data/keithito/LJSpeech-1.1/ ../tmp/
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python3 distribute.py --config_path config.json --data_path /data/ro/shared/data/keithito/LJSpeech-1.1/
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# python3 distribute.py --config_path config.json --data_path /data/ro/shared/data/keithito/LJSpeech-1.1/
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# cp -R ${USER_DIR}/Mozilla_22050 ../tmp/
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# python3 distribute.py --config_path config_tacotron_gst.json --data_path ../tmp/Mozilla_22050/
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python3 distribute.py --config_path config.json --data_path /data/rw/home/LibriTTS/train-clean-360
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# python3 distribute.py --config_path config.json --data_path /data/rw/home/LibriTTS/train-clean-360
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python3 distribute.py --config_path config.json
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while true; do sleep 1000000; done
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@ -1,6 +1,6 @@
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{
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"run_name": "ljspeech",
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"run_description": "Tacotron prenet fix test run - dev-memory_fix",
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"run_description": "Tacotron2 ljspeech release training",
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"audio":{
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// Audio processing parameters
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@ -31,7 +31,7 @@
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"reinit_layers": [],
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"model": "Tacotron", // one of the model in models/
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"model": "Tacotron2", // one of the model in models/
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"grad_clip": 1, // upper limit for gradients for clipping.
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"epochs": 1000, // total number of epochs to train.
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"lr": 0.0001, // Initial learning rate. If Noam decay is active, maximum learning rate.
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@ -82,7 +82,7 @@
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[
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{
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"name": "ljspeech",
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"path": "/home/erogol/Data/LJSpeech-1.1/",
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"path": "/data/ro/shared/data/keithito/LJSpeech-1.1/",
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"meta_file_train": "metadata_train.csv",
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"meta_file_val": "metadata_val.csv"
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}
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