| # Pre-trained Conformer-CTC models for the librispeech dataset with icefall. | |
| The model was trained on full [LibriSpeech](http://openslr.org/12/) with the scripts in [icefall](https://github.com/k2-fsa/icefall). | |
| See (https://github.com/k2-fsa/icefall/pull/13) for more details of this model. | |
| ## How to use | |
| See (https://github.com/k2-fsa/icefall/blob/master/egs/librispeech/ASR/conformer_ctc/README.md) | |
| ## Training procedure | |
| The version of the mainly repositories are list below. | |
| k2: https://github.com/k2-fsa/k2/commit/81cec9ec736d2c603ad75d933bb3e3a3706fb0dd | |
| icefall: https://github.com/k2-fsa/icefall/commit/ef233486ae6d21bacb940de45efb35d0c334605c | |
| lhotse: https://github.com/lhotse-speech/lhotse/commit/5dfe0f4c02b1334ebb7db6d67e1141fe406ca76b | |
| * 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. | |
| * Clone icefall(https://github.com/k2-fsa/icefall) and check to the commit showed above. | |
| ``` | |
| git clone https://github.com/k2-fsa/icefall | |
| cd icefall | |
| git checkout ef233486 | |
| ``` | |
| * Preparing data. | |
| ``` | |
| cd egs/librispeech/ASR | |
| bash ./prepare.sh | |
| ``` | |
| * Training | |
| ```bash | |
| export CUDA_VISIBLE_DEVICES="0,1,2,3" | |
| python conformer_ctc/train.py --bucketing-sampler True \ | |
| --concatenate-cuts False \ | |
| --max-duration 200 \ | |
| --full-libri True \ | |
| --world-size 4 | |
| ``` | |
| ## Evaluation results | |
| 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. | |
| ||test-clean|test-other| | |
| |--|--|--| | |
| |WER|2.57%|5.94%| | |