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--- |
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license: apache-2.0 |
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language: |
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- en |
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--- |
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# Pre-trained Conformer-CTC models for the librispeech dataset with icefall. |
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The model was trained on full [LibriSpeech](http://openslr.org/12/) with the scripts in [icefall](https://github.com/k2-fsa/icefall). |
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See (https://github.com/k2-fsa/icefall/pull/13) for more details of this model. |
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## How to use |
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See (https://github.com/k2-fsa/icefall/blob/master/egs/librispeech/ASR/conformer_ctc/README.md) |
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## Training procedure |
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The version of the mainly repositories are list below. |
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k2: https://github.com/k2-fsa/k2/commit/81cec9ec736d2c603ad75d933bb3e3a3706fb0dd |
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icefall: https://github.com/k2-fsa/icefall/commit/ef233486ae6d21bacb940de45efb35d0c334605c |
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lhotse: https://github.com/lhotse-speech/lhotse/commit/5dfe0f4c02b1334ebb7db6d67e1141fe406ca76b |
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* 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. It is better to use the given version above, but I think the latest version would be ok. And also install the requirements listed in icefall. |
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* Clone icefall(https://github.com/k2-fsa/icefall) and check to the commit showed above. |
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``` |
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git clone https://github.com/k2-fsa/icefall |
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cd icefall |
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git checkout ef233486 |
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``` |
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* Preparing data. |
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``` |
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cd egs/librispeech/ASR |
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bash ./prepare.sh |
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``` |
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* Training |
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```bash |
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export CUDA_VISIBLE_DEVICES="0,1,2,3" |
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python conformer_ctc/train.py --bucketing-sampler True \ |
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--concatenate-cuts False \ |
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--max-duration 200 \ |
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--full-libri True \ |
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--world-size 4 |
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``` |
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## Evaluation results |
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The best decoding results (WERs) on LibriSpeech test-clean and test-other are listed below, we got this results by averaging models from epoch 15 to 34. |
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||test-clean|test-other| |
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|--|--|--| |
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|WER|2.57%|5.94%| |
