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---
tags:
- espnet
- audio
---
Repository: `ms180/mini_an4_integration_test`
## Training
- System: `ASRSystem`
- Recipe: `mini_an4/asr`
- Creator: `ms180`
- Created: `2026-01-14T00:36:01.951598`
- Git: `8509faad9811b58d5024f29fb9d68ffb026b5e73` (dirty)
## Pack
- Archive: `model_pack`
- Strategy: `espnet3`
- Exp dir: `exp/train_asr_rnn_data_aug_debug`
## Train config
<details><summary>expand</summary>
```
num_device: 1
num_nodes: 1
task: espnet3.systems.asr.task.ASRTask
recipe_dir: .
data_dir: ./data
exp_tag: train_asr_rnn_data_aug_debug
exp_dir: ./exp/train_asr_rnn_data_aug_debug
stats_dir: ./exp/stats
decode_dir: ./exp/train_asr_rnn_data_aug_debug/decode
dataset_dir: ./data/mini_an4
create_dataset:
func: src.create_dataset.create_dataset
dataset_dir: ./data/mini_an4
archive_path: ./../../egs2/mini_an4/asr1/downloads.tar.gz
dataset:
_target_: espnet3.components.data.data_organizer.DataOrganizer
train:
- name: train_nodev
dataset:
_target_: src.dataset.MiniAN4Dataset
manifest_path: ./data/mini_an4/manifest/train_nodev.tsv
valid:
- name: train_dev
dataset:
_target_: src.dataset.MiniAN4Dataset
manifest_path: ./data/mini_an4/manifest/train_dev.tsv
preprocessor:
_target_: espnet2.train.preprocessor.CommonPreprocessor
_convert_: all
fs: 16000
train: true
data_aug_effects:
- - 0.1
- contrast
- enhancement_amount: 75.0
- - 0.1
- highpass
- cutoff_freq: 5000
Q: 0.707
- - 0.1
- equalization
- center_freq: 1000
gain: 0
Q: 0.707
- - 0.1
- - - 0.3
- speed_perturb
- factor: 0.9
- - 0.3
- speed_perturb
- factor: 1.1
- - 0.3
- speed_perturb
- factor: 1.3
data_aug_num:
- 1
- 4
data_aug_prob: 1.0
token_type: bpe
token_list: ./data/bpe_30/tokens.txt
bpemodel: ./data/bpe_30/bpe.model
parallel:
env: local
n_workers: 1
dataloader:
collate_fn:
_target_: espnet2.train.collate_fn.CommonCollateFn
int_pad_value: -1
train:
multiple_iterator: false
num_shards: 1
iter_factory:
_target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory
shuffle: true
collate_fn:
_target_: espnet2.train.collate_fn.CommonCollateFn
int_pad_value: -1
num_workers: 0
batches:
type: sorted
shape_files:
- ./exp/stats/train/feats_shape
batch_size: 2
batch_bins: 200000
valid:
multiple_iterator: false
num_shards: 1
iter_factory:
_target_: espnet2.iterators.sequence_iter_factory.SequenceIterFactory
shuffle: false
collate_fn:
_target_: espnet2.train.collate_fn.CommonCollateFn
int_pad_value: -1
batches:
type: sorted
shape_files:
- ./exp/stats/valid/feats_shape
batch_size: 2
batch_bins: 200000
optim:
_target_: torch.optim.Adam
lr: 0.001
weight_decay: 0.0
scheduler:
_target_: torch.optim.lr_scheduler.ReduceLROnPlateau
mode: min
factor: 0.5
patience: 1
val_scheduler_criterion: valid/loss
best_model_criterion:
- - valid/acc
- 1
- max
trainer:
accelerator: auto
devices: 1
num_nodes: 1
accumulate_grad_batches: 1
check_val_every_n_epoch: 1
gradient_clip_val: 1.0
log_every_n_steps: 1
max_epochs: 1
limit_train_batches: 1
limit_val_batches: 1
precision: 32
logger:
- _target_: lightning.pytorch.loggers.TensorBoardLogger
save_dir: ./exp/train_asr_rnn_data_aug_debug/tensorboard
name: tb_logger
strategy: auto
tokenizer:
vocab_size: 30
character_coverage: 1.0
model_type: bpe
save_path: ./data/bpe_30
text_builder:
func: src.tokenizer.gather_training_text
manifest_path: ./data/mini_an4/manifest/train_nodev.tsv
model:
vocab_size: 30
token_list: ./data/bpe_30/tokens.txt
encoder: vgg_rnn
encoder_conf:
num_layers: 1
hidden_size: 2
output_size: 2
decoder: rnn
decoder_conf:
hidden_size: 2
normalize: utterance_mvn
normalize_conf: {}
model_conf:
ctc_weight: 0.3
lsm_weight: 0.1
length_normalized_loss: false
frontend: default
frontend_conf:
n_fft: 512
win_length: 400
hop_length: 160
```
</details>
### Citing ESPnet
```
@inproceedings{watanabe2018espnet,
author={Shinji Watanabe and Takaaki Hori and Shigeki Karita and Tomoki Hayashi and
Jiro Nishitoba and Yuya Unno and Nelson Yalta and Jahn Heymann and Matthew Wiesner
and Nanxin Chen and Adithya Renduchintala and Tsubasa Ochiai},
title={{ESPnet}: End-to-End Speech Processing Toolkit},
year={2018},
booktitle={Proceedings of Interspeech},
pages={2207--2211},
doi={10.21437/Interspeech.2018-1456}
}
```
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