
## ESPnet2 ASR model 

### `Fhrozen/test_an4`

This model was trained by Fhrozen using an4 recipe in [espnet](https://github.com/espnet/espnet/).

### Demo: How to use in ESPnet2

```bash
cd espnet
git checkout b8df4c928e132acff78d196988bdb68a66987952
pip install -e .
cd egs2/an4/asr1
./run.sh --skip_data_prep false --skip_train true --download_model Fhrozen/test_an4
```

<!-- Generated by scripts/utils/show_asr_result.sh -->
# RESULTS
## Environments
- date: `Wed Oct 20 00:00:46 JST 2021`
- python version: `3.9.7 (default, Sep 16 2021, 13:09:58)  [GCC 7.5.0]`
- espnet version: `espnet 0.10.4a1`
- pytorch version: `pytorch 1.9.0`
- Git hash: `b8df4c928e132acff78d196988bdb68a66987952`
  - Commit date: `Tue Oct 19 07:48:11 2021 -0400`

## asr_train_raw_en_bpe30
### WER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|inference_lm_lm_train_lm_en_bpe30_valid.loss.ave_asr_model_valid.acc.best/test|130|773|4.0|22.3|73.7|0.1|96.1|100.0|
|inference_lm_lm_train_lm_en_bpe30_valid.loss.ave_asr_model_valid.acc.best/train_dev|100|591|2.7|21.8|75.5|0.0|97.3|100.0|

### CER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|inference_lm_lm_train_lm_en_bpe30_valid.loss.ave_asr_model_valid.acc.best/test|130|2565|17.2|16.4|66.4|1.0|83.8|100.0|
|inference_lm_lm_train_lm_en_bpe30_valid.loss.ave_asr_model_valid.acc.best/train_dev|100|1915|15.5|16.4|68.1|0.9|85.5|100.0|

### TER

|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err|
|---|---|---|---|---|---|---|---|---|
|inference_lm_lm_train_lm_en_bpe30_valid.loss.ave_asr_model_valid.acc.best/test|130|2695|21.1|15.6|63.3|0.9|79.9|100.0|
|inference_lm_lm_train_lm_en_bpe30_valid.loss.ave_asr_model_valid.acc.best/train_dev|100|2015|19.4|15.6|65.0|0.9|81.5|100.0|

## ASR config

<details><summary>expand</summary>

```
config: null
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/asr_train_raw_en_bpe30
ngpu: 0
seed: 0
num_workers: 1
num_att_plot: 3
dist_backend: nccl
dist_init_method: env://
dist_world_size: null
dist_rank: null
local_rank: null
dist_master_addr: null
dist_master_port: null
dist_launcher: null
multiprocessing_distributed: false
unused_parameters: false
sharded_ddp: false
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
collect_stats: false
write_collected_feats: false
max_epoch: 40
patience: null
val_scheduler_criterion:
- valid
- loss
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
-   - train
    - loss
    - min
-   - valid
    - loss
    - min
-   - train
    - acc
    - max
-   - valid
    - acc
    - max
keep_nbest_models:
- 10
grad_clip: 5.0
grad_clip_type: 2.0
grad_noise: false
accum_grad: 1
no_forward_run: false
resume: true
train_dtype: float32
use_amp: false
log_interval: null
use_tensorboard: true
use_wandb: false
wandb_project: null
wandb_id: null
wandb_entity: null
wandb_name: null
wandb_model_log_interval: -1
detect_anomaly: false
pretrain_path: null
init_param: []
ignore_init_mismatch: false
freeze_param: []
num_iters_per_epoch: null
batch_size: 20
valid_batch_size: null
batch_bins: 1000000
valid_batch_bins: null
train_shape_file:
- exp/asr_stats_raw_en_bpe30/train/speech_shape
- exp/asr_stats_raw_en_bpe30/train/text_shape.bpe
valid_shape_file:
- exp/asr_stats_raw_en_bpe30/valid/speech_shape
- exp/asr_stats_raw_en_bpe30/valid/text_shape.bpe
batch_type: folded
valid_batch_type: null
fold_length:
- 80000
- 150
sort_in_batch: descending
sort_batch: descending
multiple_iterator: false
chunk_length: 500
chunk_shift_ratio: 0.5
num_cache_chunks: 1024
train_data_path_and_name_and_type:
-   - dump/raw/train_nodev/wav.scp
    - speech
    - sound
-   - dump/raw/train_nodev/text
    - text
    - text
valid_data_path_and_name_and_type:
-   - dump/raw/train_dev/wav.scp
    - speech
    - sound
-   - dump/raw/train_dev/text
    - text
    - text
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
valid_max_cache_size: null
optim: adadelta
optim_conf: {}
scheduler: null
scheduler_conf: {}
token_list:
- <blank>
- <unk>
- ▁
- T
- E
- O
- R
- Y
- A
- H
- U
- S
- I
- F
- B
- L
- P
- D
- G
- M
- C
- V
- X
- J
- K
- Z
- W
- N
- Q
- <sos/eos>
init: null
input_size: null
ctc_conf:
    dropout_rate: 0.0
    ctc_type: builtin
    reduce: true
    ignore_nan_grad: true
model_conf:
    ctc_weight: 0.5
    ignore_id: -1
    lsm_weight: 0.0
    length_normalized_loss: false
    report_cer: true
    report_wer: true
    sym_space: <space>
    sym_blank: <blank>
    extract_feats_in_collect_stats: true
use_preprocessor: true
token_type: bpe
bpemodel: data/en_token_list/bpe_unigram30/bpe.model
non_linguistic_symbols: null
cleaner: null
g2p: null
speech_volume_normalize: null
rir_scp: null
rir_apply_prob: 1.0
noise_scp: null
noise_apply_prob: 1.0
noise_db_range: '13_15'
frontend: default
frontend_conf:
    fs: 16k
specaug: null
specaug_conf: {}
normalize: global_mvn
normalize_conf:
    stats_file: exp/asr_stats_raw_en_bpe30/train/feats_stats.npz
preencoder: null
preencoder_conf: {}
encoder: rnn
encoder_conf: {}
postencoder: null
postencoder_conf: {}
decoder: rnn
decoder_conf: {}
required:
- output_dir
- token_list
version: 0.10.4a1
distributed: false
```

</details>

## LM config
    
<details><summary>expand</summary>

```
  config: conf/train_lm.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/lm_train_lm_en_bpe30
ngpu: 0
seed: 0
num_workers: 1
num_att_plot: 3
dist_backend: nccl
dist_init_method: env://
dist_world_size: null
dist_rank: null
local_rank: null
dist_master_addr: null
dist_master_port: null
dist_launcher: null
multiprocessing_distributed: false
unused_parameters: false
sharded_ddp: false
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
collect_stats: false
write_collected_feats: false
max_epoch: 40
patience: null
val_scheduler_criterion:
- valid
- loss
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
-   - valid
    - loss
    - min
keep_nbest_models: 1
grad_clip: 5.0
grad_clip_type: 2.0
grad_noise: false
accum_grad: 1
no_forward_run: false
resume: true
train_dtype: float32
use_amp: false
log_interval: null
use_tensorboard: true
use_wandb: false
wandb_project: null
wandb_id: null
wandb_entity: null
wandb_name: null
wandb_model_log_interval: -1
detect_anomaly: false
pretrain_path: null
init_param: []
ignore_init_mismatch: false
freeze_param: []
num_iters_per_epoch: null
batch_size: 256
valid_batch_size: null
batch_bins: 1000000
valid_batch_bins: null
train_shape_file:
- exp/lm_stats_en_bpe30/train/text_shape.bpe
valid_shape_file:
- exp/lm_stats_en_bpe30/valid/text_shape.bpe
batch_type: folded
valid_batch_type: null
fold_length:
- 150
sort_in_batch: descending
sort_batch: descending
multiple_iterator: false
chunk_length: 500
chunk_shift_ratio: 0.5
num_cache_chunks: 1024
train_data_path_and_name_and_type:
-   - dump/raw/lm_train.txt
    - text
    - text
valid_data_path_and_name_and_type:
-   - dump/raw/train_dev/text
    - text
    - text
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
valid_max_cache_size: null
optim: adam
optim_conf:
    lr: 0.1
scheduler: null
scheduler_conf: {}
token_list:
- <blank>
- <unk>
- ▁
- T
- E
- O
- R
- Y
- A
- H
- U
- S
- I
- F
- B
- L
- P
- D
- G
- M
- C
- V
- X
- J
- K
- Z
- W
- N
- Q
- <sos/eos>
init: null
model_conf:
    ignore_id: 0
use_preprocessor: true
token_type: bpe
bpemodel: data/en_token_list/bpe_unigram30/bpe.model
non_linguistic_symbols: null
cleaner: null
g2p: null
lm: seq_rnn
lm_conf:
    unit: 650
    nlayers: 2
required:
- output_dir
- token_list
version: 0.10.4a1
distributed: false
```

</details>
    

{"language": "en", "license": "cc-by-4.0", "tags": ["espnet", "audio", "automatic-speech-recognition"], "datasets": ["an4"]}
espnet audio automatic-speech-recognition en dataset:an4 license:cc-by-4.0 region:us
TAGS
#espnet #audio #automatic-speech-recognition #en #dataset-an4 #license-cc-by-4.0 #region-us 

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


### 'Fhrozen/test\_an4'


This model was trained by Fhrozen using an4 recipe in espnet.


### Demo: How to use in ESPnet2


RESULTS
=======


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


* date: 'Wed Oct 20 00:00:46 JST 2021'
* python version: '3.9.7 (default, Sep 16 2021, 13:09:58) [GCC 7.5.0]'
* espnet version: 'espnet 0.10.4a1'
* pytorch version: 'pytorch 1.9.0'
* Git hash: 'b8df4c928e132acff78d196988bdb68a66987952'
	+ Commit date: 'Tue Oct 19 07:48:11 2021 -0400'


asr\_train\_raw\_en\_bpe30
--------------------------


### WER



### CER



### TER



ASR config
----------


expand

LM config
---------


expand


### 'Fhrozen/test\_an4'


This model was trained by Fhrozen using an4 recipe in espnet. ### Demo: How to use in ESPnet2


RESULTS
=======


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


* date: 'Wed Oct 20 00:00:46 JST 2021'
* python version: '3.9.7 (default, Sep 16 2021, 13:09:58) [GCC 7.5.0]'
* espnet version: 'espnet 0.10.4a1'
* pytorch version: 'pytorch 1.9.0'
* Git hash: 'b8df4c928e132acff78d196988bdb68a66987952'
	+ Commit date: 'Tue Oct 19 07:48:11 2021 -0400'


asr\_train\_raw\_en\_bpe30
-------------------------- ### WER ### CER ### TER



ASR config
----------


expand

LM config
---------


expand
TAGS
#espnet #audio #automatic-speech-recognition #en #dataset-an4 #license-cc-by-4.0 #region-us 
 ### 'Fhrozen/test\_an4'


This model was trained by Fhrozen using an4 recipe in espnet. ### Demo: How to use in ESPnet2


RESULTS
=======


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


* date: 'Wed Oct 20 00:00:46 JST 2021'
* python version: '3.9.7 (default, Sep 16 2021, 13:09:58) [GCC 7.5.0]'
* espnet version: 'espnet 0.10.4a1'
* pytorch version: 'pytorch 1.9.0'
* Git hash: 'b8df4c928e132acff78d196988bdb68a66987952'
	+ Commit date: 'Tue Oct 19 07:48:11 2021 -0400'


asr\_train\_raw\_en\_bpe30
-------------------------- ### WER ### CER ### TER



ASR config
----------


expand

LM config
---------


expand
passage: TAGS
#espnet #audio #automatic-speech-recognition #en #dataset-an4 #license-cc-by-4.0 #region-us 
### 'Fhrozen/test\_an4'


This model was trained by Fhrozen using an4 recipe in espnet.### Demo: How to use in ESPnet2


RESULTS
=======


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


* date: 'Wed Oct 20 00:00:46 JST 2021'
* python version: '3.9.7 (default, Sep 16 2021, 13:09:58) [GCC 7.5.0]'
* espnet version: 'espnet 0.10.4a1'
* pytorch version: 'pytorch 1.9.0'
* Git hash: 'b8df4c928e132acff78d196988bdb68a66987952'
	+ Commit date: 'Tue Oct 19 07:48:11 2021 -0400'


asr\_train\_raw\_en\_bpe30
--------------------------### WER### CER### TER



ASR config
----------


expand

LM config
---------


expand