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icefall/egs/librispeech/ASR/transducer_stateless
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Fangjun Kuang 4c1b3665ee
Use optimized_transducer to compute transducer loss. (#162) 
* WIP: Use optimized_transducer to compute transducer loss.

* Minor fixes.

* Fix decoding.

* Fix decoding.

* Add RESULTS.

* Update RESULTS.

* Update CI.

* Fix sampling rate for yesno recipe.
2022-01-10 11:54:58 +08:00
..
__init__.py
RNN-T Conformer training for LibriSpeech (#143)
2021-12-18 07:42:51 +08:00
asr_datamodule.py
RNN-T Conformer training for LibriSpeech (#143)
2021-12-18 07:42:51 +08:00
beam_search.py
Use optimized_transducer to compute transducer loss. (#162)
2022-01-10 11:54:58 +08:00
conformer.py
Remove batchnorm, weight decay, and SOS from transducer conformer encoder (#155)
2021-12-27 16:01:10 +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
Remove batchnorm, weight decay, and SOS from transducer conformer encoder (#155)
2021-12-27 16:01:10 +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
Use optimized_transducer to compute transducer loss. (#162)
2022-01-10 11:54:58 +08:00
model.py
Use optimized_transducer to compute transducer loss. (#162)
2022-01-10 11:54:58 +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
subsampling.py
RNN-T Conformer training for LibriSpeech (#143)
2021-12-18 07:42:51 +08:00
test_decoder.py
Increase the size of the context in the RNN-T decoder. (#153)
2021-12-23 07:55:02 +08:00
train.py
Remove batchnorm, weight decay, and SOS from transducer conformer encoder (#155)
2021-12-27 16:01:10 +08:00
transformer.py
Remove batchnorm, weight decay, and SOS from transducer conformer encoder (#155)
2021-12-27 16:01:10 +08:00

README.md

Introduction

The decoder, i.e., the prediction network, is from https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9054419 (Rnn-Transducer with Stateless Prediction Network)

You can use the following command to start the training:

cd egs/librispeech/ASR

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

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