## Results ### AIShell training results (Conformer-CTC) #### 2021-11-17 (Wei Kang): Result of https://github.com/k2-fsa/icefall/pull/30 (Pinfeng Luo): Result of https://github.com/k2-fsa/icefall/pull/30 Pretrained model is available at https://huggingface.co/pfluo/icefall_aishell_model The tensorboard log for training is available at https://tensorboard.dev/experiment/zsw6Hn6EQlG8I7HqEkiQpw The best decoding results (CER) are listed below, we got this results by averaging models from epoch 30 to 49, and using `attention-decoder` decoder with num_paths equals to 100. ||test| |--|--| |CER| 4.38% | ||lm_scale|attention_scale| |--|--|--| |test|0.6|1.2| You can use the following commands to reproduce our results: ```bash git clone https://github.com/k2-fsa/icefall cd icefall cd egs/aishell/ASR ./prepare.sh export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7" python3 conformer_ctc/train.py --bucketing-sampler False \ --concatenate-cuts False \ --max-duration 200 \ --world-size 8 python3 conformer_ctc/decode.py --lattice-score-scale 0.5 \ --epoch 49 \ --avg 20 \ --method attention-decoder \ --max-duration 50 \ --num-paths 100 ```