icefall

If you have pre-downloaded the LibriSpeech dataset, please read ./prepare.sh and modify it to point to the location of your dataset so that it won't re-download it. After modification, please run

./prepare.sh

The script ./prepare.sh prepares features, lexicon, LMs, etc. All generated files are saved in the folder ./data.

HINT: ./prepare.sh support options --stage and --stop-stage.

TDNN-LSTM CTC training

The folder tdnn_lstm_ctc contains scripts for CTC training with TDNN-LSTM models.

Pre-configured parameters for training and decoding are set in the function get_params() within tdnn_lstm_ctc/train.py and tdnn_lstm_ctc/decode.py.

Parameters that can be passed from the commandline can be found by

./tdnn_lstm_ctc/train.py --help
./tdnn_lstm_ctc/decode.py --help

If you have 4 GPUs on a machine and want to use GPU 0, 2, 3 for mutli-GPU training, you can run

export CUDA_VISIBLE_DEVICES="0,2,3"
./tdnn_lstm_ctc/train.py \
  --master-port 12345 \
  --world-size 3

If you want to decode by averaging checkpoints epoch-8.pt, epoch-9.pt and epoch-10.pt, you can run

./tdnn_lstm_ctc/decode.py \
  --epoch 10 \
  --avg 3

Conformer CTC training

The folder conformer-ctc contains scripts for CTC training with conformer models. The steps of running the training and decoding are similar as tdnn_lstm_ctc.