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Update results
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@ -13,8 +13,9 @@ ln -sfv /path/to/GigaSpeech download/GigaSpeech
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```
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```
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## Performance Record
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## Performance Record
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| | Dev | Test |
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| | Dev | Test |
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|-----|-------|-------|
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|--------------------------------|-------|-------|
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| WER | 10.47 | 10.58 |
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| `conformer_ctc` | 10.47 | 10.58 |
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| `pruned_transducer_stateless2` | 10.52 | 10.62 |
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See [RESULTS](/egs/gigaspeech/ASR/RESULTS.md) for details.
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See [RESULTS](/egs/gigaspeech/ASR/RESULTS.md) for details.
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@ -1,4 +1,70 @@
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## Results
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## Results
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### GigaSpeech BPE training results (Pruned Transducer 2)
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#### 2022-05-12
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Results are:
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| | Dev | Test |
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|----------------------|-------|-------|
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| greedy search | 10.59 | 10.87 |
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| fast beam search | 10.56 | 10.80 |
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| modified beam search | 10.52 | 10.62 |
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To reproduce the above result, use the following commands for training:
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```
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cd egs/gigaspeech/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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./pruned_transducer_stateless2/train.py \
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--max-duration 120 \
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--num-workers 1 \
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--world-size 8 \
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--exp-dir pruned_transducer_stateless2/exp \
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--bpe-model data/lang_bpe_500/bpe.model \
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--use-fp16 True
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```
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and the following commands for decoding:
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```
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# greedy search
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./pruned_transducer_stateless2/decode.py \
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--epoch 29 \
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--avg 11 \
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--decoding-method greedy_search \
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--exp-dir pruned_transducer_stateless2/exp \
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--bpe-model data/lang_bpe_500/bpe.model \
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--max-duration 20 \
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--num-workers 1
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# fast beam search
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./pruned_transducer_stateless2/decode.py \
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--epoch 29 \
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--avg 9 \
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--decoding-method fast_beam_search \
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--exp-dir pruned_transducer_stateless2/exp \
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--bpe-model data/lang_bpe_500/bpe.model \
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--max-duration 20 \
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--num-workers 1
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# modified beam search
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./pruned_transducer_stateless2/decode.py \
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--epoch 29 \
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--avg 8 \
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--decoding-method modified_beam_search \
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--exp-dir pruned_transducer_stateless2/exp \
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--bpe-model data/lang_bpe_500/bpe.model \
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--max-duration 20 \
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--num-workers 1
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```
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Pretrained model is available at
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<https://huggingface.co/wgb14/icefall-asr-gigaspeech-pruned-transducer-stateless2>
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The tensorboard log for training is available at
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<https://tensorboard.dev/experiment/zmmM0MLASnG1N2RmJ4MZBw/>
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### GigaSpeech BPE training results (Conformer-CTC)
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### GigaSpeech BPE training results (Conformer-CTC)
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@ -98,14 +98,14 @@ def get_parser():
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parser.add_argument(
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parser.add_argument(
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"--epoch",
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"--epoch",
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type=int,
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type=int,
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default=28,
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default=29,
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help="It specifies the checkpoint to use for decoding."
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help="It specifies the checkpoint to use for decoding."
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"Note: Epoch counts from 0.",
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"Note: Epoch counts from 0.",
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)
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)
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parser.add_argument(
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parser.add_argument(
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"--avg",
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"--avg",
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type=int,
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type=int,
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default=15,
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default=8,
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help="Number of checkpoints to average. Automatically select "
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help="Number of checkpoints to average. Automatically select "
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"consecutive checkpoints before the checkpoint specified by "
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"consecutive checkpoints before the checkpoint specified by "
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"'--epoch'. ",
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"'--epoch'. ",
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@ -111,7 +111,7 @@ def get_parser():
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parser.add_argument(
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parser.add_argument(
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"--num-epochs",
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"--num-epochs",
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type=int,
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type=int,
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default=20,
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default=30,
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help="Number of epochs to train.",
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help="Number of epochs to train.",
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)
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)
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