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