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* Disable weight decay. * Remove input feature batchnorm.. * Replace BatchNorm in the Conformer model with LayerNorm. * Use tanh in the joint network. * Remove sos ID. * Reduce the number of decoder layers from 4 to 2. * Minor fixes. * Fix typos.
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