--- tags: - espnet - audio - self-supervised-learning language: en datasets: - librispeech license: cc-by-4.0 --- ## ESPnet2 SSL model ### `espnet/hubert_large_gs_16_librilight60k` This model was trained by wanchichen using librispeech recipe in [espnet](https://github.com/espnet/espnet/). ### Demo: How to use in ESPnet2 Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html) if you haven't done that already. ```bash cd espnet pip install -e . cd egs2/librispeech/ssl1 ./run.sh --skip_data_prep false --skip_train true --download_model espnet/hubert_large_gs_16_librilight60k ``` ## SSL config
expand ``` config: conf/tuning/train_ssl_torchaudiohubert_large_960h_pretrain_it2_bins.yaml print_config: false log_level: INFO dry_run: false iterator_type: sequence output_dir: exp/hubert_iter1_train_ssl_torchaudiohubert_large_960h_pretrain_it2_bins_raw ngpu: 1 seed: 0 num_workers: 16 num_att_plot: 3 dist_backend: nccl dist_init_method: env:// dist_world_size: 8 dist_rank: 0 local_rank: 0 dist_master_addr: localhost dist_master_port: 55415 dist_launcher: null multiprocessing_distributed: true unused_parameters: true sharded_ddp: false cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: true collect_stats: false write_collected_feats: false max_epoch: 190 patience: null val_scheduler_criterion: - valid - loss early_stopping_criterion: - valid - loss - min best_model_criterion: - - valid - loss - min keep_nbest_models: 10 nbest_averaging_interval: 0 grad_clip: 5.0 grad_clip_type: 2.0 grad_noise: false accum_grad: 16 no_forward_run: false resume: true train_dtype: float32 use_amp: true 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 pretrain_path: null init_param: [] ignore_init_mismatch: false freeze_param: [] num_iters_per_epoch: 40000 batch_size: 20 valid_batch_size: null batch_bins: 100000 valid_batch_bins: null train_shape_file: - exp/hubert_iter1_stats_raw/splits16/speech_shape - exp/hubert_iter1_stats_raw/splits16/text_shape.word valid_shape_file: - exp/hubert_iter1_stats_raw/valid/speech_shape - exp/hubert_iter1_stats_raw/valid/text_shape.word batch_type: numel valid_batch_type: null fold_length: - 80000 - 400 sort_in_batch: descending sort_batch: descending multiple_iterator: true chunk_length: 500 chunk_shift_ratio: 0.5 num_cache_chunks: 1024 train_data_path_and_name_and_type: - - exp/hubert_iter1_stats_raw/splits16/wav.scp - speech - sound - - exp/hubert_iter1_stats_raw/splits16/text.km.kmeans_iter1_hubert_train_60k_portion0.1_gigaspeech - text - text valid_data_path_and_name_and_type: - - dump/raw/dev/wav.scp - speech - sound - - dump/raw/dev/text.km.kmeans_iter1_hubert_train_60k_portion0.1_gigaspeech - text - text allow_variable_data_keys: false max_cache_size: 0.0 max_cache_fd: 32 valid_max_cache_size: null exclude_weight_decay: false exclude_weight_decay_conf: {} optim: adam optim_conf: lr: 0.0005 scheduler: warmuplr scheduler_conf: warmup_steps: 32000 token_list: - '6' - '185' - '233' - '206' - '200' - '47' - '129' - '362' - '436' - '50' - '30' - '137' - '39' - '126' - '81' - '78' - '444' - '439' - '230' - '33' - '14' - '61' - '450' - '239' - '293' - '161' - '410' - '355' - '262' - '475' - '338' - '201' - '242' - '318' - '159' - '56' - '190' - '21' - '259' - '458' - '187' - '268' - '7' - '398' - '67' - '11' - '455' - '241' - '4' - '261' - '412' - '388' - '402' - '414' - '180' - '41' - '198' - '100' - '459' - '96' - '235' - '267' - '203' - '189' - '60' - '160' - '64' - '300' - '295' - '473' - '37' - '130' - '77' - '424' - '369' - '217' - '366' - '3' - '82' - '149' - '330' - '79' - '351' - '223' - '446' - '269' - '148' - '186' - '110' - '62' - '471' - '316' - '433' - '127' - '354' - '243' - '457' - '240' - '375' - '46' - '40' - '339' - '224' - '183' - '179' - '357' - '430' - '83' - '49' - '154' - '237' - '460' - '353' - '289' - '92' - '109' - '311' - '71' - '391' - '406' - '43' - '73' - '418' - '437' - '250' - '463' - '120' - '346' - '146' - '454' - '211' - '274' - '167' - '345' - '10' - '68' - '348' - '244' - '102' - '474' - '192' - '144' - '112' - '25' - '449' - '308' - '405' - '48' - '212' - '205' - '124' - '153' - '9' - '5' - '258' - '306' - '80' - '394' - '328' - '208' - '166' - '36' - '352' - '18' - '397' - '66' - '31' - '16' - '426' - '332' - '23' - '281' - '215' - '88' - '171' - '221' - '184' - '202' - '470' - '247' - '38' - '389' - '315' - '197' - '349' - '304' - '393' - '380' - '132' - '456' - '367' - '479' - '360' - '123' - '162' - '365' - '337' - '467' - '234' - '364' - '376' - '173' - '478' - '425' - '218' - '297' - '469' - '282' - '298' - '451' - '20' - '117' - '52' - '113' - '165' - '280' - '292' - '226' - '104' - '55' - '145' - '286' - '86' - '294' - '15' - '216' - '279' - '275' - '253' - '312' - '378' - '287' - '76' - '168' - '116' - '368' - '396' - '336' - '290' - '53' - '103' - '0' - '411' - '228' - '408' - '285' - '151' - '325' - '193' - '428' - '401' - '320' - '182' - '480' - '264' - '383' - '114' - '115' - '374' - '141' - '22' - '466' - '384' - '174' - '59' - '326' - '105' - '232' - '464' - '251' - '24' - '172' - '150' - '299' - '89' - '344' - '427' - '333' - '434' - '107' - '291' - '194' - '497' - '452' - '317' - '254' - '213' - '499' - '483' - '432' - '95' - '321' - '111' - '8' - '175' - '277' - '65' - '342' - '382' - '301' - '45' - '443' - '63' - '93' - '489' - '74' - '387' - '370' - '340' - '358' - '220' - '429' - '2' - '331' - '181' - '32' - '324' - '191' - '238' - '313' - '157' - '91' - '101' - '118' - '350' - '356' - '486' - '188' - '142' - '419' - '195' - '164' - '487' - '255' - '323' - '222' - '35' - '245' - '359' - '249' - '98' - '271' - '231' - '125' - '29' - '34' - '119' - '134' - '284' - '309' - '409' - '422' - '147' - '484' - '462' - '390' - '440' - '283' - '84' - '108' - '139' - '170' - '303' - '371' - '381' - '278' - '329' - '28' - '87' - '403' - '256' - '441' - '334' - '12' - '260' - '265' - '69' - '122' - '488' - '99' - '42' - '302' - '97' - '70' - '152' - '177' - '138' - '296' - '51' - '491' - '199' - '176' - '204' - '169' - '386' - '494' - '400' - '341' - '229' - '273' - '485' - '135' - '227' - '54' - '314' - '343' - '477' - '465' - '482' - '257' - '435' - '423' - '121' - '496' - '448' - '453' - '85' - '57' - '276' - '210' - '272' - '236' - '407' - '445' - '90' - '266' - '490' - '307' - '155' - '136' - '19' - '319' - '498' - '163' - '75' - '442' - '495' - '421' - '209' - '361' - '156' - '395' - '472' - '415' - '347' - '252' - '468' - '476' - '106' - '143' - '263' - '373' - '327' - '322' - '399' - '404' - '13' - '288' - '207' - '58' - '481' - '131' - '385' - '447' - '219' - '438' - '461' - '416' - '246' - '417' - '26' - '158' - '431' - '270' - '128' - '413' - '310' - '140' - '17' - '392' - '44' - '27' - '214' - '377' - '305' - '72' - '420' - '133' - '363' - '379' - '94' - '225' - '335' - '493' - '492' - '372' - '196' - '248' - '178' - '1' - - init: null collate_fn_conf: label_downsampling: 1 pad: false rand_crop: true input_size: 1 num_classes: 500 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' pred_masked_weight: 1.0 pred_nomask_weight: 0.0 loss_weights: 0.0 frontend: null frontend_conf: {} specaug: null specaug_conf: {} normalize: null normalize_conf: {} preencoder: null preencoder_conf: {} encoder: torchaudio_hubert encoder_conf: encoder_projection_dropout: 0.0 encoder_attention_dropout: 0.0 encoder_ff_interm_dropout: 0.0 encoder_dropout: 0.0 encoder_layer_drop: 0.0 extractor_mode: layer_norm encoder_embed_dim: 1024 encoder_num_layers: 24 encoder_num_heads: 16 encoder_ff_interm_features: 4096 encoder_layer_norm_first: true normalize_feats: true final_dim: 768 model: torchaudio model_conf: {} required: - output_dir - token_list version: '202301' distributed: true ```
### Citing ESPnet ```BibTex @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: ```bibtex @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} } ```