
## ESPnet2 ASR model

### `espnet/wanchichen_fleurs_multilingual_asr_hubert_frontend`
This model was trained by William Chen using the fleurs recipe in [espnet](https://github.com/espnet/espnet/).
### Demo: How to use in ESPnet2
```bash
cd espnet
pip install -e .
cd egs2/fleurs/asr1
./run.sh
```

<!-- Generated by scripts/utils/show_asr_result.sh -->
# RESULTS
## Environments
- date: `Sun Aug 21 15:18:30 EDT 2022`
- python version: `3.8.6 (default, Dec 17 2020, 16:57:01)  [GCC 10.2.0]`
- espnet version: `espnet 202205`
- pytorch version: `pytorch 1.8.1+cu102`
- Git hash: `45e8cb9173a072f85ee7a7ccbcae06af7c5c484a`
  - Commit date: `Wed Jun 1 14:21:14 2022 +0900`

## asr_train_asr_hubert_raw_all_raw_all_bpe6500_sp
### WER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|decode_asr_asr_model_valid.acc.best/test_all|77809|1669969|54.2|38.1|7.8|4.0|49.9|99.7|
|decode_asr_asr_model_valid.acc.best/dev_all|31622|610500|53.4|38.7|7.9|3.5|50.1|99.5|

### CER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|decode_asr_asr_model_valid.acc.best/test_all|77809|10876592|85.1|7.4|7.5|3.2|18.0|99.7|
|decode_asr_asr_model_valid.acc.best/dev_all|31622|3988181|84.7|7.7|7.7|2.8|18.1|99.5|

### TER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|decode_asr_asr_model_valid.acc.best/test_all|77809|9622352|82.8|9.2|8.0|3.4|20.6|99.7|
|decode_asr_asr_model_valid.acc.best/dev_all|31622|3547834|82.4|9.4|8.2|3.0|20.6|99.5|
{"language": "en", "license": "cc-by-4.0", "tags": ["espnet", "audio", "speech-recognition"], "datasets": ["google/fleurs"]}
espnet audio speech-recognition en dataset:google/fleurs license:cc-by-4.0 region:us
TAGS
#espnet #audio #speech-recognition #en #dataset-google/fleurs #license-cc-by-4.0 #region-us 

ESPnet2 ASR model
-----------------


### 'espnet/wanchichen\_fleurs\_multilingual\_asr\_hubert\_frontend'


This model was trained by William Chen using the fleurs recipe in espnet.


### Demo: How to use in ESPnet2


RESULTS
=======


Environments
------------


* date: 'Sun Aug 21 15:18:30 EDT 2022'
* python version: '3.8.6 (default, Dec 17 2020, 16:57:01) [GCC 10.2.0]'
* espnet version: 'espnet 202205'
* pytorch version: 'pytorch 1.8.1+cu102'
* Git hash: '45e8cb9173a072f85ee7a7ccbcae06af7c5c484a'
	+ Commit date: 'Wed Jun 1 14:21:14 2022 +0900'


asr\_train\_asr\_hubert\_raw\_all\_raw\_all\_bpe6500\_sp
--------------------------------------------------------


### WER



### CER



### TER




### 'espnet/wanchichen\_fleurs\_multilingual\_asr\_hubert\_frontend'


This model was trained by William Chen using the fleurs recipe in espnet. ### Demo: How to use in ESPnet2


RESULTS
=======


Environments
------------


* date: 'Sun Aug 21 15:18:30 EDT 2022'
* python version: '3.8.6 (default, Dec 17 2020, 16:57:01) [GCC 10.2.0]'
* espnet version: 'espnet 202205'
* pytorch version: 'pytorch 1.8.1+cu102'
* Git hash: '45e8cb9173a072f85ee7a7ccbcae06af7c5c484a'
	+ Commit date: 'Wed Jun 1 14:21:14 2022 +0900'


asr\_train\_asr\_hubert\_raw\_all\_raw\_all\_bpe6500\_sp
-------------------------------------------------------- ### WER ### CER ### TER
TAGS
#espnet #audio #speech-recognition #en #dataset-google/fleurs #license-cc-by-4.0 #region-us 
 ### 'espnet/wanchichen\_fleurs\_multilingual\_asr\_hubert\_frontend'


This model was trained by William Chen using the fleurs recipe in espnet. ### Demo: How to use in ESPnet2


RESULTS
=======


Environments
------------


* date: 'Sun Aug 21 15:18:30 EDT 2022'
* python version: '3.8.6 (default, Dec 17 2020, 16:57:01) [GCC 10.2.0]'
* espnet version: 'espnet 202205'
* pytorch version: 'pytorch 1.8.1+cu102'
* Git hash: '45e8cb9173a072f85ee7a7ccbcae06af7c5c484a'
	+ Commit date: 'Wed Jun 1 14:21:14 2022 +0900'


asr\_train\_asr\_hubert\_raw\_all\_raw\_all\_bpe6500\_sp
-------------------------------------------------------- ### WER ### CER ### TER
passage: TAGS
#espnet #audio #speech-recognition #en #dataset-google/fleurs #license-cc-by-4.0 #region-us 
### 'espnet/wanchichen\_fleurs\_multilingual\_asr\_hubert\_frontend'


This model was trained by William Chen using the fleurs recipe in espnet.### Demo: How to use in ESPnet2


RESULTS
=======


Environments
------------


* date: 'Sun Aug 21 15:18:30 EDT 2022'
* python version: '3.8.6 (default, Dec 17 2020, 16:57:01) [GCC 10.2.0]'
* espnet version: 'espnet 202205'
* pytorch version: 'pytorch 1.8.1+cu102'
* Git hash: '45e8cb9173a072f85ee7a7ccbcae06af7c5c484a'
	+ Commit date: 'Wed Jun 1 14:21:14 2022 +0900'


asr\_train\_asr\_hubert\_raw\_all\_raw\_all\_bpe6500\_sp
--------------------------------------------------------### WER### CER### TER