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72 lines
2.1 KiB
Markdown
72 lines
2.1 KiB
Markdown
## Results
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### TedLium3 BPE training results (Transducer)
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#### Conformer encoder + embedding decoder
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Using the codes from this PR https://github.com/k2-fsa/icefall/pull/233
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And the SpecAugment codes from this PR https://github.com/lhotse-speech/lhotse/pull/604
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Conformer encoder + non-current decoder. The decoder
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contains only an embedding layer and a Conv1d (with kernel size 2).
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The WERs are
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| | dev | test | comment |
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|------------------------------------|------------|------------|------------------------------------------|
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| greedy search | 7.19 | 6.57 | --epoch 29, --avg 16, --max-duration 100 |
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| beam search (beam size 4) | 7.12 | 6.37 | --epoch 29, --avg 16, --max-duration 100 |
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| modified beam search (beam size 4) | 7.00 | 6.19 | --epoch 29, --avg 16, --max-duration 100 |
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The training command for reproducing is given below:
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```
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export CUDA_VISIBLE_DEVICES="0,1,2,3"
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./transducer_stateless/train.py \
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--world-size 4 \
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--num-epochs 30 \
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--start-epoch 0 \
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--exp-dir transducer_stateless/exp \
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--max-duration 200
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```
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The tensorboard training log can be found at
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https://tensorboard.dev/experiment/zrfXeJO3Q5GmJpP2KRd2VA/#scalars
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The decoding command is:
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```
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epoch=29
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avg=16
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## greedy search
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./transducer_stateless/decode.py \
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--epoch $epoch \
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--avg $avg \
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--exp-dir transducer_stateless/exp \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--max-duration 100
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## beam search
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./transducer_stateless/decode.py \
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--epoch $epoch \
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--avg $avg \
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--exp-dir transducer_stateless/exp \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--max-duration 100 \
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--decoding-method beam_search \
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--beam-size 4
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## modified beam search
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./transducer_stateless/decode.py \
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--epoch $epoch \
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--avg $avg \
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--exp-dir transducer_stateless/exp \
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--bpe-model ./data/lang_bpe_500/bpe.model \
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--max-duration 100 \
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--decoding-method modified_beam_search \
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--beam-size 4
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```
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A pre-trained model and decoding logs can be found at <https://huggingface.co/luomingshuang/icefall_asr_tedlium3_transducer_stateless>
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