ESPnet2 ASR model

`espnet/marathi_openslr64`

This model was trained by Sujay Suresh Kumar using mr_openslr64 recipe in espnet.

Demo: How to use in ESPnet2

cd espnet
git checkout 91325a1e58ca0b13494b94bf79b186b095fe0b58
pip install -e .
cd egs2/mr_openslr64/asr1
./run.sh --skip_data_prep false --skip_train true --download_model espnet/marathi_openslr64

RESULTS

Environments

date: Mon Mar 21 16:06:03 UTC 2022
python version: 3.9.7 (default, Sep 16 2021, 13:09:58) [GCC 7.5.0]
espnet version: espnet 0.10.7a1
pytorch version: pytorch 1.11.0+cu102
Git hash: 91325a1e58ca0b13494b94bf79b186b095fe0b58
- Commit date: Mon Mar 21 00:40:52 2022 +0000

asr_train_asr_conformer_xlsr_raw_bpe150_sp

WER

dataset	Snt	Wrd	Corr	Sub	Del	Ins	Err	S.Err
decode_asr_batch_size1_asr_model_valid.acc.ave/marathi_test	299	3625	72.9	22.5	4.7	1.7	28.9	88.6

CER

dataset	Snt	Wrd	Corr	Sub	Del	Ins	Err	S.Err
decode_asr_batch_size1_asr_model_valid.acc.ave/marathi_test	299	20557	91.4	3.1	5.5	1.9	10.5	88.6

TER

dataset	Snt	Wrd	Corr	Sub	Del	Ins	Err	S.Err
decode_asr_batch_size1_asr_model_valid.acc.ave/marathi_test	299	13562	86.5	6.3	7.1	1.4	14.9	88.6

ASR config

expand

config: conf/tuning/train_asr_conformer_xlsr.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/asr_train_asr_conformer_xlsr_raw_bpe150_sp
ngpu: 1
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: 0
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: 60
patience: null
val_scheduler_criterion:
- valid
- loss
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
-   - valid
    - acc
    - max
keep_nbest_models: 5
nbest_averaging_interval: 0
grad_clip: 5.0
grad_clip_type: 2.0
grad_noise: false
accum_grad: 3
no_forward_run: false
resume: true
train_dtype: float32
use_amp: false
log_interval: null
use_matplotlib: true
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:
- frontend.upstream
num_iters_per_epoch: null
batch_size: 20
valid_batch_size: null
batch_bins: 10000
valid_batch_bins: null
train_shape_file:
- exp/asr_stats_raw_bpe150_sp/train/speech_shape
- exp/asr_stats_raw_bpe150_sp/train/text_shape.bpe
valid_shape_file:
- exp/asr_stats_raw_bpe150_sp/valid/speech_shape
- exp/asr_stats_raw_bpe150_sp/valid/text_shape.bpe
batch_type: numel
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/marathi_train_sp/wav.scp
    - speech
    - sound
-   - dump/raw/marathi_train_sp/text
    - text
    - text
valid_data_path_and_name_and_type:
-   - dump/raw/marathi_dev/wav.scp
    - speech
    - sound
-   - dump/raw/marathi_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: 0.0005
scheduler: warmuplr
scheduler_conf:
    warmup_steps: 20000
token_list:
- <blank>
- <unk>
- ▁
- ा
- ी
- े
- त
- र
- ं
- न
- क
- ्
- व
- ि
- ल
- ▁म
- स
- ो
- श
- द
- च
- म
- ▁अ
- ▁आ
- ण
- ु
- ला
- ह
- ▁आहे
- य
- ▁स
- ग
- ▁ह
- ्या
- चा
- ▁प
- ड
- ▁क
- प
- ट
- ▁ब
- ज
- र्
- ्र
- ▁?
- ▁ज
- ब
- ून
- वा
- ▁एक
- ▁या
- ळ
- ात
- ख
- ध
- ▁ति
- ठ
- ल्या
- ले
- ू
- ▁तुम्हाला
- ां
- ार
- घ
- ची
- ▁अस
- थ
- ▁का
- ने
- णि
- ॅ
- ▁त
- ▁परवा
- ▁ते
- ली
- ▁गेल
- ळा
- ष
- ▁कर
- .
- च्या
- ▁न
- वर
- ▁त्या
- ▁प्र
- ▁करू
- ▁ग
- ्ट
- ई
- झ
- ▁फ
- ाय
- क्ष
- ▁काय
- पूर
- ▁होती
- मध
- ▁तिथ
- ▁काही
- ए
- ▁वि
- ▁दोन
- ▁महिन्या
- व्हा
- तील
- जार
- ▁नाही
- ँ
- ▁पुत
- ॉ
- ▁झाला
- ▁दिसल
- ▁साल
- ▁रस्त्यावर
- स्त
- जवळ
- न्म
- मध्य
- ऊ
- ▁इथे
- ▁तुमच
- ▁शकते
- मान
- ▁उद्
- फ
- ै
- ढ
- ','
- इ
- ौ
- ‍
- ृ
- ओ
- ः
- ॲ
- आ
- '-'
- ञ
- औ
- '!'
- ऑ
- ऱ
- ऐ
- छ
- उ
- '?'
- भ
- अ
- ऋ
- <sos/eos>
init: xavier_uniform
input_size: null
ctc_conf:
    dropout_rate: 0.0
    ctc_type: builtin
    reduce: true
    ignore_nan_grad: true
joint_net_conf: null
use_preprocessor: true
token_type: bpe
bpemodel: data/token_list/bpe_unigram150/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: s3prl
frontend_conf:
    frontend_conf:
        upstream: wav2vec2_xlsr
    download_dir: ./hub
    multilayer_feature: true
    fs: 16k
specaug: specaug
specaug_conf:
    apply_time_warp: true
    time_warp_window: 5
    time_warp_mode: bicubic
    apply_freq_mask: true
    freq_mask_width_range:
    - 0
    - 30
    num_freq_mask: 2
    apply_time_mask: true
    time_mask_width_range:
    - 0
    - 40
    num_time_mask: 2
normalize: utterance_mvn
normalize_conf: {}
model: espnet
model_conf:
    ctc_weight: 0.3
    lsm_weight: 0.1
    length_normalized_loss: false
    extract_feats_in_collect_stats: false
preencoder: linear
preencoder_conf:
    input_size: 1024
    output_size: 80
encoder: conformer
encoder_conf:
    output_size: 512
    attention_heads: 4
    linear_units: 1024
    num_blocks: 3
    dropout_rate: 0.3
    positional_dropout_rate: 0.3
    attention_dropout_rate: 0.3
    input_layer: conv2d
    normalize_before: true
    macaron_style: false
    pos_enc_layer_type: rel_pos
    selfattention_layer_type: rel_selfattn
    activation_type: swish
    use_cnn_module: true
    cnn_module_kernel: 17
postencoder: null
postencoder_conf: {}
decoder: transformer
decoder_conf:
    attention_heads: 4
    linear_units: 1024
    num_blocks: 3
    dropout_rate: 0.3
    positional_dropout_rate: 0.3
    self_attention_dropout_rate: 0.3
    src_attention_dropout_rate: 0.3
required:
- output_dir
- token_list
version: 0.10.7a1
distributed: false

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},
  url={http://dx.doi.org/10.21437/Interspeech.2018-1456}
}

or arXiv:

@misc{watanabe2018espnet,
  title={ESPnet: End-to-End Speech Processing Toolkit}, 
  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},
  year={2018},
  eprint={1804.00015},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}