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End2End

#ESPnet

  1. python timit_wrd.py for changing TIMIT's word into broad phone labels.

  2. run espnet/egs/timit/asr1/run.sh until stage 2 for preparing data.json.

  3. python gen_fbank.py to generate the FBank feature in txt file.

  4. copy-feats ark,t:fbank.txt ark,scp:fbank.ark,fbank.scp

  5. python change_data.py to modify fbank feature in data.json.

  6. run espnet/egs/timit/asr1/run.sh --stage 3 for new ASR model with new fbank.

  7. copy the pre-trained model from espnet. cp /espnet/egs/timit/asr_fbank/exp/train_nodev_pytorch_train/results/model.loss.best.entire PytorchSE/data/newctcloss.model.acc.best.entire.pth

#Pytorch SE 1.modify PATHS in the run.sh

2.sh run.sh

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