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espnet
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hubert_dummy

ESPnet
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audio
self-supervised-learning
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ESPnet2 SSL model

espnet/hubert_dummy

This model was trained by chen26 using librispeech recipe in espnet.

Demo: How to use in ESPnet2

Follow the ESPnet installation instructions if you haven't done that already.

cd espnet

pip install -e .
cd egs2/librispeech/ssl1
./run.sh --skip_data_prep false --skip_train true --download_model espnet/hubert_dummy

SSL config

expand 
config: conf/tuning/train_hubert_dummy.yaml
print_config: false
log_level: INFO
drop_last_iter: false
dry_run: false
iterator_type: sequence
valid_iterator_type: null
output_dir: exp/ssl_train_hubert_dummy_raw
ngpu: 1
seed: 0
num_workers: 4
num_att_plot: 0
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
use_deepspeed: true
deepspeed_config: conf/deepspeed.json
gradient_as_bucket_view: true
ddp_comm_hook: null
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
use_tf32: false
collect_stats: false
write_collected_feats: false
max_epoch: 1
patience: null
val_scheduler_criterion:
- valid
- loss
early_stopping_criterion:
- valid
- loss
- min
best_model_criterion:
-   - valid
    - total_count
    - max
keep_nbest_models: 5
nbest_averaging_interval: 0
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_matplotlib: true
use_tensorboard: true
create_graph_in_tensorboard: false
use_wandb: false
wandb_project: null
wandb_id: null
wandb_entity: null
wandb_name: null
wandb_model_log_interval: -1
detect_anomaly: false
use_adapter: false
adapter: lora
save_strategy: all
adapter_conf: {}
pretrain_path: null
init_param: []
ignore_init_mismatch: false
freeze_param: []
num_iters_per_epoch: 10
batch_size: 20
valid_batch_size: null
batch_bins: 16000
valid_batch_bins: null
category_sample_size: 10
train_shape_file:
- exp/ssl_stats_raw/train/speech_shape
valid_shape_file:
- exp/ssl_stats_raw/valid/speech_shape
batch_type: numel
valid_batch_type: null
fold_length:
- 80000
- 400
sort_in_batch: descending
shuffle_within_batch: false
sort_batch: descending
multiple_iterator: false
chunk_length: 500
chunk_shift_ratio: 0.5
num_cache_chunks: 1024
chunk_excluded_key_prefixes: []
chunk_default_fs: null
chunk_max_abs_length: null
chunk_discard_short_samples: true
train_data_path_and_name_and_type:
-   - dump/raw/train_960/wav.scp
    - speech
    - sound
-   - dump/raw/train_960/text
    - text
    - text
valid_data_path_and_name_and_type:
-   - dump/raw/dev/wav.scp
    - speech
    - sound
-   - dump/raw/dev/text
    - text
    - text
multi_task_dataset: false
allow_variable_data_keys: false
max_cache_size: 0.0
max_cache_fd: 32
allow_multi_rates: false
valid_max_cache_size: null
exclude_weight_decay: false
exclude_weight_decay_conf: {}
optim: adadelta
optim_conf: {}
scheduler: null
scheduler_conf: {}
token_list:
- '30'
- '4'
- '72'
- '305'
- '275'
- '24'
- '369'
- '125'
- '202'
- '368'
- '270'
- '296'
- '68'
- '188'
- '418'
- '223'
- '8'
- '338'
- '437'
- '14'
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- '469'
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- '44'
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- '449'
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- '130'
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- '96'
- '162'
- '456'
- '84'
- '98'
- '217'
- '48'
- '482'
- '127'
- '110'
- '366'
- '336'
- '387'
- '105'
- '373'
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- '119'
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- '216'
- '104'
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- '38'
- '382'
- '238'
- '474'
- '225'
- '465'
- '309'
- '17'
- '285'
- '90'
- '375'
- '356'
- '256'
- '392'
- '311'
- '398'
- '9'
- '264'
- '341'
- '168'
- '339'
- '40'
- '344'
- '422'
- '63'
- '396'
- '51'
- '184'
- '441'
- '346'
- '252'
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- '444'
- '198'
- '66'
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- '5'
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- '15'
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- '166'
- '304'
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- '329'
- '395'
- '413'
- '435'
- '33'
- '266'
- '133'
- '210'
- '408'
- '330'
- '315'
- '251'
- '6'
- '357'
- '171'
- '56'
- '1'
- '59'
- '359'
- '28'
- '215'
- '97'
- '274'
- '170'
- '49'
- '81'
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- '364'
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- '433'
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- '2'
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- '26'
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- '412'
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- '201'
- '361'
- '232'
- '290'
- '109'
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- '438'
- '64'
- '447'
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- '301'
- '249'
- '186'
- '234'
- '121'
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- '255'
- '82'
- '384'
- '160'
- '494'
- '351'
- '283'
- '32'
- '54'
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- '132'
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- '302'
- '348'
- '136'
- '451'
- '479'
- '183'
- '45'
- '404'
- '263'
- '477'
- '355'
- '29'
- '414'
- '237'
- '409'
- '385'
- '461'
- '386'
- '124'
- '401'
- '352'
- '293'
- '471'
- '458'
- '472'
- '486'
- '164'
- '453'
- '310'
- '207'
- '487'
- '294'
- '360'
- '245'
- '242'
- '431'
- '250'
- <unk>
- <sos/eos>
init: null
collate_fn_conf:
    label_downsampling: 1
    pad: false
    rand_crop: true
input_size: null
num_classes: null
use_preprocessor: true
token_type: word
bpemodel: null
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'
window_size: null
window_shift: null
loss:
-   name: hubert
    conf:
        num_classes: 500
        final_dim: 2
util:
-   name: mask
    conf: {}
frontend: wav2vec_cnn
frontend_conf:
    norm_mode: group_norm
    conv_mode: standard
    bias: false
    normalize_audio: false
    shapes:
    -   - 2
        - 1
        - 10
    fs: 16k
specaug: null
specaug_conf: {}
normalize: null
normalize_conf: {}
preencoder: linear
preencoder_conf:
    output_size: 16
encoder: transformer
encoder_conf:
    output_size: 16
    attention_heads: 1
    linear_units: 4
    num_blocks: 2
    dropout_rate: 0.1
    positional_dropout_rate: 0.0
    attention_dropout_rate: 0.1
    input_layer: wav2vec
    normalize_before: false
    pos_enc_layer_type: conv
model: espnet
model_conf: {}
required:
- output_dir
- token_list
version: '202412'
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}
}
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