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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 |
|