Note: This recipe is trained with the codes from this PR https://github.com/k2-fsa/icefall/pull/399 # Pre-trained Transducer-Stateless5 models for the AISHELL4 dataset with icefall. The model was trained on the far data of [AISHELL4](https://www.openslr.org/111) with the scripts in [icefall](https://github.com/k2-fsa/icefall) based on the latest version k2. ## Training procedure The main repositories are list below, we will update the training and decoding scripts with the update of version. k2: https://github.com/k2-fsa/k2 icefall: https://github.com/k2-fsa/icefall lhotse: https://github.com/lhotse-speech/lhotse * Install k2 and lhotse, k2 installation guide refers to https://k2.readthedocs.io/en/latest/installation/index.html, lhotse refers to https://lhotse.readthedocs.io/en/latest/getting-started.html#installation. I think the latest version would be ok. And please also install the requirements listed in icefall. * Clone icefall(https://github.com/k2-fsa/icefall) and check to the commit showed above. ``` git clone https://github.com/k2-fsa/icefall cd icefall ``` * Preparing data. ``` cd egs/aishell4/ASR bash ./prepare.sh ``` * Training ``` export CUDA_VISIBLE_DEVICES="0,1,2,3" ./pruned_transducer_stateless5/train.py \ --world-size 4 \ --num-epochs 30 \ --start-epoch 1 \ --exp-dir pruned_transducer_stateless5/exp \ --lang-dir data/lang_char \ --max-duration 220 ``` ## Evaluation results The decoding results (CER%) on AISHELL4(test) are listed below: When use-averaged-model=False, the CERs are | | test | comment | |------------------------------------|------------|------------------------------------------| | greedy search | 30.05 | --epoch 30, --avg 25, --max-duration 800 | | modified beam search (beam size 4) | 29.16 | --epoch 30, --avg 25, --max-duration 800 | | fast beam search (set as default) | 29.20 | --epoch 30, --avg 25, --max-duration 1500| When use-averaged-model=True, the CERs are | | test | comment | |------------------------------------|------------|----------------------------------------------------------------------| | greedy search | 29.89 | --iter 36000, --avg 8, --max-duration 800 --use-averaged-model=True | | modified beam search (beam size 4) | 28.91 | --iter 36000, --avg 8, --max-duration 800 --use-averaged-model=True | | fast beam search (set as default) | 29.08 | --iter 36000, --avg 8, --max-duration 1500 --use-averaged-model=True |