readme: Note: This recipe is trained with the codes from this PR https://github.com/k2-fsa/icefall/pull/233
  And the SpecAugment codes from this PR https://github.com/lhotse-speech/lhotse/pull/604.
  
  # Pre-trained Transducer-Stateless models for the TEDLium3 dataset with icefall.
  The model was trained on full [TEDLium3](https://www.openslr.org/51) with the scripts in [icefall](https://github.com/k2-fsa/icefall).  
  ## 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/tedlium3/ASR
  bash ./prepare.sh
  ```
  * Training
  ```
  export CUDA_VISIBLE_DEVICES="0,1,2,3"
  ./transducer_stateless/train.py \
                    --world-size 4 \
                    --num-epochs 30 \
                    --start-epoch 0 \
                    --exp-dir transducer_stateless/exp \
                    --max-duration 300
  ```
  ## Evaluation results
  The decoding results (WER%) on TEDLium3 (dev and test) are listed below, we got this result by averaging models from epoch 19 to 29.
  The WERs are
  |                                    |     dev    |    test    | comment                                  |
  |------------------------------------|------------|------------|------------------------------------------|
  |          greedy search             | 7.19       | 6.70       | --epoch 29, --avg 11, --max-duration 100 |
  |      beam search (beam size 4)     | 7.02       | 6.36       | --epoch 29, --avg 11, --max-duration 100 |
  | modified beam search (beam size 4) | 6.91       | 6.33       | --epoch 29, --avg 11, --max-duration 100 |
  