# Efficient Conformer v1 for non-streaming ASR

**Specification**: https://github.com/wenet-e2e/wenet/pull/1636

## Results

* Feature info:
    * using fbank feature, cmvn, speed perturb, dither
* Training info:
    * train_u2++_efficonformer_v1.yaml
    * 8 gpu, batch size 16, acc_grad 1, 120 epochs
    * lr 0.001, warmup_steps 35000
* Model info:
    * Model Params: 49,474,974
    * Downsample rate: 1/4 (conv2d) * 1/2 (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

test clean

| decoding mode          | full | 18   | 16   |
|------------------------|------|------|------|
| attention decoder      | 3.65 | 3.88 | 3.87 |
| ctc_greedy_search      | 3.46 | 3.79 | 3.77 |
| ctc prefix beam search | 3.44 | 3.75 | 3.74 |
| attention rescoring    | 3.17 | 3.44 | 3.41 |

test other

| decoding mode          | full | 18    | 16    |
|------------------------|------|-------|-------|
| attention decoder      | 8.51 | 9.24  | 9.25  |
| ctc_greedy_search      | 8.94 | 10.04 | 10.06 |
| ctc prefix beam search | 8.91 | 10    | 10.01 |
| attention rescoring    | 8.21 | 9.25  | 9.25  |


## Start to Use

Install **WeNet** follow: https://wenet.org.cn/wenet/install.html#install-for-training


Decode
```sh
cd examples/librispeech/s0

cp exp/wenet_efficient_conformer_librispeech_v1/decode.sh ./
cp exp/wenet_efficient_conformer_librispeech_v1/wer.sh ./

dir=exp/wenet_efficient_conformer_librispeech_v1
decoding_chunk_size=-1
. ./decode.sh ${dir} 20 ${decoding_chunk_size}

# WER
. ./wer.sh test_clean wenet_efficient_conformer_librispeech_v1 ${decoding_chunk_size}
. ./wer.sh test_other wenet_efficient_conformer_librispeech_v1 ${decoding_chunk_size}
```



{"language": ["en", "zh"], "license": "apache-2.0", "metrics": ["cer"], "pipeline_tag": "automatic-speech-recognition"}
automatic-speech-recognition en zh license:apache-2.0 region:us
TAGS
#automatic-speech-recognition #en #zh #license-apache-2.0 #region-us 

Efficient Conformer v1 for non-streaming ASR
============================================


Specification: URL


Results
-------


* Feature info:
	+ using fbank feature, cmvn, speed perturb, dither
* Training info:
	+ train\_u2++\_efficonformer\_v1.yaml
	+ 8 gpu, batch size 16, acc\_grad 1, 120 epochs
	+ lr 0.001, warmup\_steps 35000
* Model info:
	+ Model Params: 49,474,974
	+ Downsample rate: 1/4 (conv2d) \* 1/2 (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


test clean



test other



Start to Use
------------


Install WeNet follow: URL


Decode



TAGS
#automatic-speech-recognition #en #zh #license-apache-2.0 #region-us 

TAGS
#automatic-speech-recognition #en #zh #license-apache-2.0 #region-us 
