Update README.md

README.md

@@ -1,5 +1,42 @@
-The model was trained with icefall (https://github.com/k2-fsa/icefall/pull/13), k2 (https://github.com/k2-fsa/k2/commit/81cec9ec736d2c603ad75d933bb3e3a3706fb0dd) and lhotse (https://github.com/lhotse-speech/lhotse/commit/5dfe0f4c02b1334ebb7db6d67e1141fe406ca76b)
+# Conformer-CTC model for speech recognition
+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.
 
-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
+```
+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%|