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icefall/egs/librispeech/ASR/transducer
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jaeeunbaik 915e8e399c Add CHiME-4 dataset, RIR and Self-Distillation 
- Added CHiME-4 dataset integration in asr_datamodule.py
- Added Hugging Face upload script
- Added RIR augmentation
- Added Self-Distillation Training
2025-08-27 16:11:20 +09:00
..
__init__.py
Add CHiME-4 dataset, RIR and Self-Distillation
2025-08-27 16:11:20 +09:00
asr_datamodule.py
RNN-T Conformer training for LibriSpeech (#143)
2021-12-18 07:42:51 +08:00
beam_search.py
Add CHiME-4 dataset, RIR and Self-Distillation
2025-08-27 16:11:20 +09:00
conformer.py
Fix joiner (#234)
2022-03-02 16:41:14 +08:00
decode.py
Fix style issues. (#937)
2023-03-08 22:56:04 +08:00
decoder.py
Add CHiME-4 dataset, RIR and Self-Distillation
2025-08-27 16:11:20 +09:00
encoder_interface.py
Fix joiner (#234)
2022-03-02 16:41:14 +08:00
export.py
Use tokens.txt to replace bpe.model (#1162)
2023-08-12 16:53:59 +08:00
joiner.py
Add CHiME-4 dataset, RIR and Self-Distillation
2025-08-27 16:11:20 +09:00
model.py
Add CHiME-4 dataset, RIR and Self-Distillation
2025-08-27 16:11:20 +09:00
pretrained.py
Use high_freq -400 in computing fbank features. (#1447)
2024-01-04 13:59:32 +08:00
README.md
Add CHiME-4 dataset, RIR and Self-Distillation
2025-08-27 16:11:20 +09:00
rnn.py
Add CHiME-4 dataset, RIR and Self-Distillation
2025-08-27 16:11:20 +09:00
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
Ban the test_rnn.py in ci-test (#949)
2023-03-15 22:02:20 +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
formatted the entire LibriSpeech recipe (#1270)
2023-09-24 17:31:01 +08:00
transformer.py
Fix joiner (#234)
2022-03-02 16:41:14 +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