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--- |
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tags: |
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- espnet |
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- audio |
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- automatic-speech-recognition |
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language: en |
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datasets: |
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- swbd_da |
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license: cc-by-4.0 |
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--- |
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## ESPnet2 ASR model |
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### `akreal/espnet2_swbd_da_hubert_conformer` |
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This model was trained by Pavel Denisov using swbd_da recipe in [espnet](https://github.com/espnet/espnet/). |
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### Demo: How to use in ESPnet2 |
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```bash |
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cd espnet |
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git checkout 08c6efbc6299c972301236625f9abafe087c9f9c |
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pip install -e . |
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cd egs2/swbd_da/asr1 |
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./run.sh --skip_data_prep false --skip_train true --download_model espnet/akreal_swbd_da_hubert_conformer |
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``` |
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<!-- Generated by scripts/utils/show_asr_result.sh --> |
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# RESULTS |
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## Environments |
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- date: `Thu Jan 20 19:31:21 CET 2022` |
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- python version: `3.8.12 (default, Aug 30 2021, 00:00:00) [GCC 11.2.1 20210728 (Red Hat 11.2.1-1)]` |
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- espnet version: `espnet 0.10.6a1` |
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- pytorch version: `pytorch 1.10.1+cu113` |
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- Git hash: `08c6efbc6299c972301236625f9abafe087c9f9c` |
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- Commit date: `Tue Jan 4 13:40:33 2022 +0100` |
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## asr_train_asr_raw_en_word_sp |
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### WER |
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |
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|---|---|---|---|---|---|---|---|---| |
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|decode_asr_asr_model_valid.loss.ave/test_context3|2379|2379|66.3|33.7|0.0|0.0|33.7|33.7| |
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|decode_asr_asr_model_valid.loss.ave/valid_context3|8116|8116|69.5|30.5|0.0|0.0|30.5|30.5| |
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### CER |
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |
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|---|---|---|---|---|---|---|---|---| |
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|decode_asr_asr_model_valid.loss.ave/test_context3|2379|19440|76.1|17.7|6.2|8.1|32.0|33.7| |
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|decode_asr_asr_model_valid.loss.ave/valid_context3|8116|66353|79.5|16.1|4.4|8.0|28.5|30.5| |
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### TER |
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |
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|---|---|---|---|---|---|---|---|---| |
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## ASR config |
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<details><summary>expand</summary> |
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``` |
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config: conf/tuning/train_asr_conformer_hubert_context3.yaml |
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print_config: false |
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log_level: INFO |
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dry_run: false |
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iterator_type: sequence |
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output_dir: exp/asr_train_asr_conformer_hubert_context3_raw_en_word_sp |
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ngpu: 1 |
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seed: 0 |
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num_workers: 1 |
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num_att_plot: 3 |
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dist_backend: nccl |
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dist_init_method: env:// |
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dist_world_size: null |
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dist_rank: null |
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local_rank: 0 |
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dist_master_addr: null |
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dist_master_port: null |
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dist_launcher: null |
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multiprocessing_distributed: false |
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unused_parameters: false |
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sharded_ddp: false |
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cudnn_enabled: true |
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cudnn_benchmark: false |
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cudnn_deterministic: true |
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collect_stats: false |
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write_collected_feats: false |
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max_epoch: 35 |
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patience: null |
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val_scheduler_criterion: |
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- valid |
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- loss |
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early_stopping_criterion: |
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- valid |
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- loss |
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- min |
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best_model_criterion: |
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- - valid |
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- loss |
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- min |
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keep_nbest_models: 7 |
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nbest_averaging_interval: 0 |
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grad_clip: 5.0 |
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grad_clip_type: 2.0 |
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grad_noise: false |
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accum_grad: 1 |
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no_forward_run: false |
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resume: true |
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train_dtype: float32 |
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use_amp: false |
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log_interval: null |
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use_matplotlib: true |
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use_tensorboard: true |
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use_wandb: false |
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wandb_project: null |
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wandb_id: null |
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wandb_entity: null |
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wandb_name: null |
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wandb_model_log_interval: -1 |
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detect_anomaly: false |
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pretrain_path: null |
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init_param: [] |
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ignore_init_mismatch: false |
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freeze_param: |
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- frontend.upstream |
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num_iters_per_epoch: null |
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batch_size: 20 |
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valid_batch_size: null |
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batch_bins: 4000000 |
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valid_batch_bins: null |
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train_shape_file: |
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- exp/asr_stats_context3_raw_en_word_sp/train/speech_shape |
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- exp/asr_stats_context3_raw_en_word_sp/train/text_shape.word |
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valid_shape_file: |
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- exp/asr_stats_context3_raw_en_word_sp/valid/speech_shape |
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- exp/asr_stats_context3_raw_en_word_sp/valid/text_shape.word |
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batch_type: numel |
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valid_batch_type: null |
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fold_length: |
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- 80000 |
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- 150 |
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sort_in_batch: descending |
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sort_batch: descending |
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multiple_iterator: false |
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chunk_length: 500 |
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chunk_shift_ratio: 0.5 |
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num_cache_chunks: 1024 |
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train_data_path_and_name_and_type: |
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- - dump/raw/train_context3_sp/wav.scp |
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- speech |
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- sound |
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- - dump/raw/train_context3_sp/text |
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- text |
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- text |
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valid_data_path_and_name_and_type: |
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- - dump/raw/valid_context3/wav.scp |
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- speech |
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- sound |
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- - dump/raw/valid_context3/text |
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- text |
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- text |
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allow_variable_data_keys: false |
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max_cache_size: 0.0 |
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max_cache_fd: 32 |
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valid_max_cache_size: null |
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optim: adam |
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optim_conf: |
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lr: 0.0001 |
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scheduler: warmuplr |
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scheduler_conf: |
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warmup_steps: 25000 |
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token_list: |
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- <blank> |
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- <unk> |
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- statement |
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- backchannel |
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- opinion |
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- abandon |
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- agree |
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- yn_q |
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- apprec |
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- 'yes' |
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- uninterp |
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- close |
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- wh_q |
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- acknowledge |
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- 'no' |
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- yn_decl_q |
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- hedge |
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- backchannel_q |
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- sum |
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- quote |
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- affirm |
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- other |
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- directive |
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- repeat |
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- open_q |
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- completion |
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- rhet_q |
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- hold |
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- reject |
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- answer |
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- neg |
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- ans_dispref |
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- repeat_q |
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- open |
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- or |
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- commit |
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- maybe |
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- decl_q |
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- third_pty |
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- self_talk |
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- thank |
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- apology |
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- tag_q |
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- downplay |
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- <sos/eos> |
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init: null |
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input_size: null |
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ctc_conf: |
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dropout_rate: 0.0 |
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ctc_type: builtin |
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reduce: true |
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ignore_nan_grad: true |
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joint_net_conf: null |
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model_conf: |
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ctc_weight: 0.0 |
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extract_feats_in_collect_stats: false |
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use_preprocessor: true |
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token_type: word |
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bpemodel: null |
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non_linguistic_symbols: null |
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cleaner: null |
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g2p: null |
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speech_volume_normalize: null |
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rir_scp: null |
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rir_apply_prob: 1.0 |
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noise_scp: null |
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noise_apply_prob: 1.0 |
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noise_db_range: '13_15' |
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frontend: s3prl |
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frontend_conf: |
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frontend_conf: |
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upstream: hubert_large_ll60k |
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download_dir: ./hub |
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multilayer_feature: true |
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fs: 16k |
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specaug: specaug |
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specaug_conf: |
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apply_time_warp: true |
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time_warp_window: 5 |
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time_warp_mode: bicubic |
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apply_freq_mask: true |
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freq_mask_width_range: |
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- 0 |
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- 30 |
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num_freq_mask: 2 |
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apply_time_mask: true |
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time_mask_width_range: |
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- 0 |
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- 40 |
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num_time_mask: 2 |
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normalize: utterance_mvn |
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normalize_conf: {} |
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preencoder: linear |
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preencoder_conf: |
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input_size: 1024 |
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output_size: 80 |
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encoder: conformer |
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encoder_conf: |
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output_size: 512 |
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attention_heads: 8 |
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linear_units: 2048 |
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num_blocks: 12 |
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dropout_rate: 0.1 |
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positional_dropout_rate: 0.1 |
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attention_dropout_rate: 0.1 |
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input_layer: conv2d |
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normalize_before: true |
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macaron_style: true |
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pos_enc_layer_type: rel_pos |
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selfattention_layer_type: rel_selfattn |
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activation_type: swish |
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use_cnn_module: true |
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cnn_module_kernel: 31 |
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postencoder: null |
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postencoder_conf: {} |
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decoder: transformer |
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decoder_conf: |
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attention_heads: 8 |
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linear_units: 2048 |
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num_blocks: 6 |
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dropout_rate: 0.1 |
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positional_dropout_rate: 0.1 |
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self_attention_dropout_rate: 0.1 |
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src_attention_dropout_rate: 0.1 |
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required: |
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- output_dir |
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- token_list |
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version: 0.10.5a1 |
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distributed: false |
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``` |
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</details> |
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### Citing ESPnet |
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```BibTex |
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@inproceedings{watanabe2018espnet, |
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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}, |
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title={{ESPnet}: End-to-End Speech Processing Toolkit}, |
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year={2018}, |
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booktitle={Proceedings of Interspeech}, |
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pages={2207--2211}, |
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doi={10.21437/Interspeech.2018-1456}, |
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url={http://dx.doi.org/10.21437/Interspeech.2018-1456} |
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} |
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``` |
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or arXiv: |
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```bibtex |
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@misc{watanabe2018espnet, |
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title={ESPnet: End-to-End Speech Processing Toolkit}, |
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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}, |
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year={2018}, |
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eprint={1804.00015}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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