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Add README.md and RESULTS.md
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egs/timit/ASR/README.md
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Please refer to <https://icefall.readthedocs.io/en/latest/recipes/timit.html>
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for how to run models in this recipe.
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## Results
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### TIMIT training results (Tdnn_LSTM_CTC)
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#### 2021-11-16
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(Mingshuang Luo): Result of https://github.com/k2-fsa/icefall/pull/114
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TensorBoard log is available at https://tensorboard.dev/experiment/qhA1o025Q322kO34SlhWzg/#scalars
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Pretrained model is available at https://huggingface.co/luomingshuang/icefall_asr_timit_tdnn_lstm_ctc
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The best decoding results (PER) are listed below, we got this results by averaging models from epoch 16 to 25, and using `whole-lattice-rescoring` with lm_scale equals to 0.08.
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||TEST|
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|--|--|
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|PER| 19.71% |
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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/timit/ASR
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./prepare.sh
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export CUDA_VISIBLE_DEVICES="0"
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python tdnn_lstm_ctc/train.py --bucketing-sampler True \
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--concatenate-cuts False \
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--max-duration 200 \
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--world-size 1 \
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--lang-dir data/lang_phone
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python tdnn_lstm_ctc/decode.py --epoch 25 \
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--avg 10 \
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--max-duration 20 \
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--lang-dir data/lang_phone
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```
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### TIMIT training results (Tdnn_LiGRU_CTC)
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#### 2021-11-16
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(Mingshuang Luo): Result of phone based Tdnn_LiGRU_CTC model.
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Pretrained model is available at https://huggingface.co/luomingshuang/icefall_asr_timit_tdnn_ligru_ctc
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The best decoding results (PER) are listed below, we got this results by averaging models from epoch 9 to 25, and using `whole-lattice-rescoring` decoding method with lm_scale equals to 0.1.
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||TEST|
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|--|--|
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|PER| 17.66% |
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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/timit/ASR
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./prepare.sh
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export CUDA_VISIBLE_DEVICES="0"
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python tdnn_ligru_ctc/train.py --bucketing-sampler True \
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--concatenate-cuts False \
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--max-duration 200 \
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--world-size 1 \
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--lang-dir data/lang_phone
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python tdnn_ligru_ctc/decode.py --epoch 25 \
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--avg 17 \
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--max-duration 20 \
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--lang-dir data/lang_phone
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```
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