mirror of
https://github.com/k2-fsa/icefall.git
synced 2025-08-08 09:32:20 +00:00
39 lines
2.2 KiB
Markdown
39 lines
2.2 KiB
Markdown
Note: This recipe is trained with the codes from this PR https://github.com/k2-fsa/icefall/pull/375
|
|
# Pre-trained Transducer-Stateless2 models for the Aidatatang_200zh dataset with icefall.
|
|
The model was trained on full [Aidatatang_200zh](https://www.openslr.org/62) 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-fsa.github.io/k2/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/aidatatang_200zh/ASR
|
|
bash ./prepare.sh
|
|
```
|
|
* Training
|
|
```
|
|
export CUDA_VISIBLE_DEVICES="0,1"
|
|
./pruned_transducer_stateless2/train.py \
|
|
--world-size 2 \
|
|
--num-epochs 30 \
|
|
--start-epoch 0 \
|
|
--exp-dir pruned_transducer_stateless2/exp \
|
|
--lang-dir data/lang_char \
|
|
--max-duration 250
|
|
```
|
|
## Evaluation results
|
|
The decoding results (WER%) on Aidatatang_200zh(dev and test) are listed below, we got this result by averaging models from epoch 11 to 29.
|
|
The WERs are
|
|
| | dev | test | comment |
|
|
|------------------------------------|------------|------------|------------------------------------------|
|
|
| greedy search | 5.53 | 6.59 | --epoch 29, --avg 19, --max-duration 100 |
|
|
| modified beam search (beam size 4) | 5.27 | 6.33 | --epoch 29, --avg 19, --max-duration 100 |
|
|
| fast beam search (set as default) | 5.30 | 6.34 | --epoch 29, --avg 19, --max-duration 1500|
|