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@ -123,10 +123,15 @@ A tiny DeepSpeech2 **Speech-To-Text** model training on toy set of LibriSpeech:
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cd examples/tiny/s0/
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# source the environment
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source path.sh
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# prepare librispeech dataset
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bash local/data.sh
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# evaluate your ckptfile model file
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bash local/test.sh conf/deepspeech2.yaml ckptfile offline
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source ../../../utils/parse_options.sh
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# prepare data
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bash ./local/data.sh
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# train model, all `ckpt` under `exp` dir, if you use paddlepaddle-gpu, you can set CUDA_VISIBLE_DEVICES before the train script
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./local/train.sh conf/deepspeech2.yaml deepspeech2 offline
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# avg n best model to get the test model, in this case, n = 1
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avg.sh best exp/deepspeech2/checkpoints 1
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# evaluate the test model
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./local/test.sh conf/deepspeech2.yaml exp/deepspeech2/checkpoints/avg_1 offline
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```
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For **Text-To-Speech**, try pretrained FastSpeech2 + Parallel WaveGAN on CSMSC:
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