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icefall/egs/librispeech/ASR/transducer
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Fangjun Kuang 1c35ae1dba
Reset seed at the beginning of each epoch. (#221) 
* Reset seed at the beginning of each epoch.

* Use a different seed for each epoch.
2022-02-21 15:16:39 +08:00
..
__init__.py
Apply layer normalization to the output of each gate in LSTM/GRU. (#139)
2021-12-07 18:38:03 +08:00
asr_datamodule.py
RNN-T Conformer training for LibriSpeech (#143)
2021-12-18 07:42:51 +08:00
beam_search.py
Fix torch.nn.Embedding error for torch below 1.8.0 (#198)
2022-02-06 21:59:54 +08:00
conformer.py
Minor fixes to the RNN-T Conformer model (#152)
2021-12-23 13:54:25 +08:00
decode.py
Remove batchnorm, weight decay, and SOS from transducer conformer encoder (#155)
2021-12-27 16:01:10 +08:00
decoder.py
Minor fixes to the RNN-T Conformer model (#152)
2021-12-23 13:54:25 +08:00
encoder_interface.py
RNN-T Conformer training for LibriSpeech (#143)
2021-12-18 07:42:51 +08:00
export.py
Remove batchnorm, weight decay, and SOS from transducer conformer encoder (#155)
2021-12-27 16:01:10 +08:00
joiner.py
Minor fixes to the RNN-T Conformer model (#152)
2021-12-23 13:54:25 +08:00
model.py
Fix torch.nn.Embedding error for torch below 1.8.0 (#198)
2022-02-06 21:59:54 +08:00
pretrained.py
Remove batchnorm, weight decay, and SOS from transducer conformer encoder (#155)
2021-12-27 16:01:10 +08:00
README.md
RNN-T Conformer training for LibriSpeech (#143)
2021-12-18 07:42:51 +08:00
rnn.py
RNN-T Conformer training for LibriSpeech (#143)
2021-12-18 07:42:51 +08:00
subsampling.py
RNN-T Conformer training for LibriSpeech (#143)
2021-12-18 07:42:51 +08:00
test_conformer.py
Minor fixes to the RNN-T Conformer model (#152)
2021-12-23 13:54:25 +08:00
test_decoder.py
Minor fixes to the RNN-T Conformer model (#152)
2021-12-23 13:54:25 +08:00
test_joiner.py
RNN-T Conformer training for LibriSpeech (#143)
2021-12-18 07:42:51 +08:00
test_rnn.py
RNN-T Conformer training for LibriSpeech (#143)
2021-12-18 07:42:51 +08:00
test_transducer.py
Minor fixes to the RNN-T Conformer model (#152)
2021-12-23 13:54:25 +08:00
test_transformer.py
Minor fixes to the RNN-T Conformer model (#152)
2021-12-23 13:54:25 +08:00
train.py
Reset seed at the beginning of each epoch. (#221)
2022-02-21 15:16:39 +08:00
transformer.py
Minor fixes to the RNN-T Conformer model (#152)
2021-12-23 13:54:25 +08:00

README.md

Introduction

The encoder consists of Conformer layers in this folder. You can use the following command to start the training:

cd egs/librispeech/ASR

export CUDA_VISIBLE_DEVICES="0,1,2,3"

./transducer/train.py \
  --world-size 4 \
  --num-epochs 30 \
  --start-epoch 0 \
  --exp-dir transducer/exp \
  --full-libri 1 \
  --max-duration 250 \
  --lr-factor 2.5