Update README.md

README.md

@@ -1,3 +1,75 @@
 ---
 license: apache-2.0
+language:
+- en
+- zh
+metrics:
+- cer
+pipeline_tag: automatic-speech-recognition
 ---
+## Efficient Conformer v2 for non-streaming ASR
+
+**Specification**: https://github.com/wenet-e2e/wenet/pull/1636
+
+## Aishell-1 Results
+
+* Feature info:
+    * using fbank feature, cmvn, speed perturb, dither
+* Training info:
+    * [train_u2++_efficonformer_v2.yaml](https://github.com/wenet-e2e/wenet/blob/main/examples/aishell/s0/conf/train_u2%2B%2B_efficonformer_v2.yaml)
+    * 8 gpu, batch size 16, acc_grad 1, 200 epochs
+    * lr 0.001, warmup_steps 25000
+* Model info:
+    * Model Params: 49,354,651
+    * Downsample rate: 1/2 (conv2d2) * 1/4 (efficonformer block)
+    * encoder_dim 256, output_size 256, head 8, linear_units 2048
+    * num_blocks 12, cnn_module_kernel 15, group_size 3
+* Decoding info:
+    * ctc_weight 0.5, reverse_weight 0.3, average_num 20
+
+| decoding mode          | full | 18   | 16   |
+|------------------------|------|------|------|
+| attention decoder      | 4.87 | 5.03 | 5.07 |
+| ctc prefix beam search | 4.97 | 5.18 | 5.20 |
+| attention rescoring    | 4.56 | 4.75 | 4.77 |
+
+## Start to Use
+
+Install **WeNet** follow: https://wenet.org.cn/wenet/install.html#install-for-training
+
+
+Decode
+
+```sh
+cd wenet/examples/aishell/s0
+dir=exp/wenet_efficient_conformer_aishell_v2/
+
+ctc_weight=0.5
+reverse_weight=0.3
+decoding_chunk_size=-1
+mode="attention_rescoring"
+
+test_dir=$dir/test_${mode}
+mkdir -p $test_dir
+
+# Decode
+nohup python wenet/bin/recognize.py --gpu 0 \
+    --mode $mode \
+    --config $dir/train.yaml \
+    --data_type "raw" \
+    --test_data data/test/data.list \
+    --checkpoint $dir/final.pt \
+    --beam_size 10 \
+    --batch_size 1 \
+    --penalty 0.0 \
+    --dict $dir/words.txt \
+    --ctc_weight $ctc_weight \
+    --reverse_weight $reverse_weight \
+    --result_file $test_dir/text \
+    ${decoding_chunk_size:+--decoding_chunk_size $decoding_chunk_size} > logs/decode_aishell.log &
+
+# CER
+python tools/compute-cer.py --char=1 --v=1 \
+      data/test/text $test_dir/text > $test_dir/cer.txt
+```
+