mirror of https://github.com/coqui-ai/TTS.git
22 lines
1.2 KiB
Bash
22 lines
1.2 KiB
Bash
#!/bin/bash
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# take the scripts's parent's directory to prefix all the output paths.
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RUN_DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" &> /dev/null && pwd )"
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echo $RUN_DIR
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# download LJSpeech dataset
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wget http://data.keithito.com/data/speech/LJSpeech-1.1.tar.bz2
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# extract
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tar -xjf LJSpeech-1.1.tar.bz2
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# create train-val splits
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shuf LJSpeech-1.1/metadata.csv > LJSpeech-1.1/metadata_shuf.csv
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head -n 12000 LJSpeech-1.1/metadata_shuf.csv > LJSpeech-1.1/metadata_train.csv
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tail -n 1100 LJSpeech-1.1/metadata_shuf.csv > LJSpeech-1.1/metadata_val.csv
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mv LJSpeech-1.1 $RUN_DIR/
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rm LJSpeech-1.1.tar.bz2
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# compute dataset mean and variance for normalization
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python TTS/bin/compute_statistics.py $RUN_DIR/tacotron2-DDC.json $RUN_DIR/scale_stats.npy --data_path $RUN_DIR/LJSpeech-1.1/wavs/
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# training ....
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# change the GPU id if needed
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CUDA_VISIBLE_DEVICES="0" python TTS/bin/train_tacotron.py --config_path $RUN_DIR/tacotron2-DDC.json \
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--coqpit.output_path $RUN_DIR \
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--coqpit.datasets.0.path $RUN_DIR/LJSpeech-1.1/ \
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--coqpit.audio.stats_path $RUN_DIR/scale_stats.npy \ |