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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: eu |
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datasets: |
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- commonvoice |
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license: cc-by-4.0 |
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--- |
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|
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## ESPnet2 ASR model |
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### `espnet/zuazo_commonvoice_asr_train_asr_conformer5_raw_eu_bpe150_sp` |
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This model was trained by Xabier de Zuazo using commonvoice recipe in [espnet](https://github.com/espnet/espnet/). |
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### Demo: How to use in ESPnet2 |
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Follow the [ESPnet installation instructions](https://espnet.github.io/espnet/installation.html) |
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if you haven't done that already. |
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```bash |
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cd espnet |
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git checkout 5d0758e2a7063b82d1f10a8ac2de98eb6cf8a352 |
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pip install -e . |
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cd egs2/commonvoice/asr1.conformer.lm.best |
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./run.sh --skip_data_prep false --skip_train true --download_model espnet/zuazo_commonvoice_asr_train_asr_conformer5_raw_eu_bpe150_sp |
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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 Sep 21 09:55:45 CEST 2023` |
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- python version: `3.8.17 | packaged by conda-forge | (default, Jun 16 2023, 07:06:00) [GCC 11.4.0]` |
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- espnet version: `espnet 202308` |
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- pytorch version: `pytorch 2.0.1` |
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- Git hash: `5d0758e2a7063b82d1f10a8ac2de98eb6cf8a352` |
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- Commit date: `Wed Aug 30 18:03:42 2023 -0400` |
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## exp/asr_train_asr_conformer5_raw_eu_bpe150_sp |
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### WER |
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|
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |
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|---|---|---|---|---|---|---|---|---| |
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|decode_asr_lm_lm_train_lm_eu_bpe150_valid.loss.ave_asr_model_valid.acc.ave/test_eu|6640|49267|92.8|6.8|0.4|0.8|8.0|33.3| |
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|
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### CER |
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|
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |
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|---|---|---|---|---|---|---|---|---| |
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|decode_asr_lm_lm_train_lm_eu_bpe150_valid.loss.ave_asr_model_valid.acc.ave/test_eu|6640|373913|98.8|0.6|0.7|0.4|1.6|33.3| |
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|
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### TER |
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|
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |
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|---|---|---|---|---|---|---|---|---| |
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|decode_asr_lm_lm_train_lm_eu_bpe150_valid.loss.ave_asr_model_valid.acc.ave/test_eu|6640|208360|97.4|1.5|1.1|0.5|3.1|33.3| |
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|
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## exp/asr_train_asr_conformer5_raw_eu_bpe150_sp/decode_asr_lm_lm_train_lm_eu_bpe150_valid.loss.ave_asr_model_valid.acc.ave |
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### WER |
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|
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |
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|---|---|---|---|---|---|---|---|---| |
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|org/dev_eu|6640|49505|93.5|6.2|0.3|0.8|7.3|31.0| |
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|
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### CER |
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|
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |
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|---|---|---|---|---|---|---|---|---| |
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|org/dev_eu|6640|376502|99.0|0.5|0.5|0.3|1.4|31.0| |
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|
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### TER |
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|
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|dataset|Snt|Wrd|Corr|Sub|Del|Ins|Err|S.Err| |
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|---|---|---|---|---|---|---|---|---| |
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|org/dev_eu|6640|209465|97.7|1.4|1.0|0.4|2.7|31.0| |
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|
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## ASR config |
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|
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<details><summary>expand</summary> |
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``` |
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config: conf/tuning/train_asr_conformer5.yaml |
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print_config: false |
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log_level: INFO |
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drop_last_iter: false |
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dry_run: false |
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iterator_type: sequence |
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valid_iterator_type: null |
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output_dir: exp/asr_train_asr_conformer5_raw_eu_bpe150_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: 50 |
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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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- acc |
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- max |
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keep_nbest_models: 10 |
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nbest_averaging_interval: 0 |
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grad_clip: 3 |
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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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create_graph_in_tensorboard: false |
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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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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: 10000000 |
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valid_batch_bins: null |
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train_shape_file: |
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- exp/asr_stats_raw_eu_bpe150_sp/train/speech_shape |
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- exp/asr_stats_raw_eu_bpe150_sp/train/text_shape.bpe |
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valid_shape_file: |
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- exp/asr_stats_raw_eu_bpe150_sp/valid/speech_shape |
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- exp/asr_stats_raw_eu_bpe150_sp/valid/text_shape.bpe |
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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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shuffle_within_batch: false |
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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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chunk_excluded_key_prefixes: [] |
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train_data_path_and_name_and_type: |
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- - dump/raw/train_eu_sp/wav.scp |
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- speech |
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- sound |
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- - dump/raw/train_eu_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/dev_eu/wav.scp |
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- speech |
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- sound |
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- - dump/raw/dev_eu/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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exclude_weight_decay: false |
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exclude_weight_decay_conf: {} |
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optim: adam |
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optim_conf: |
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lr: 4.0 |
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scheduler: noamlr |
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scheduler_conf: |
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model_size: 256 |
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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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- A |
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- ▁ |
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- I |
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- E |
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- Z |
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- . |
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- R |
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- N |
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- U |
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- S |
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- O |
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- T |
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- KO |
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- K |
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- ▁E |
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- TU |
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- TE |
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- RA |
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- EN |
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- L |
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- ',' |
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- LA |
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- TA |
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- AK |
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- ▁A |
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- AN |
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- ▁DA |
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- RE |
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- KA |
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- P |
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- GO |
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- IN |
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- B |
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- M |
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- ▁DU |
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- RI |
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- GU |
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- ▁ETA |
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- D |
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- ER |
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- UR |
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- ▁BA |
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- ▁P |
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- H |
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- MA |
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- ▁G |
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- ▁I |
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- ▁HA |
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- TZEN |
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- LE |
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- ▁EZ |
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- ▁O |
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- EK |
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- GI |
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- ▁BAT |
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- DA |
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- DU |
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- TZA |
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- KI |
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- DI |
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- RO |
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- ▁GA |
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- REN |
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- AR |
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- TEN |
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- GA |
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- TIK |
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- RRI |
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- ▁BI |
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- LI |
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- ▁BER |
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- G |
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- ▁AR |
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- TO |
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- ERA |
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- AREN |
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- ▁ZI |
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- ▁DE |
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- ▁BE |
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- X |
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- BA |
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- ▁DI |
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- ▁IZAN |
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- ▁ZE |
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- ETAN |
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- ▁ZEN |
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- EAN |
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- IA |
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- ▁JA |
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- ▁ERE |
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- ▁DITU |
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- ▁ZA |
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- ▁ERA |
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- LO |
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- ▁HOR |
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- NTZ |
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- ▁DIRA |
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- MEN |
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- ▁HI |
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- ▁F |
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- F |
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- LDE |
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- ZIO |
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- '?' |
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- ▁ZU |
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- '-' |
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- DO |
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- ▁EGIN |
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- TZEKO |
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- ▁BEHAR |
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- TZI |
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- BIL |
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- ▁IN |
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- RIK |
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- ▁HORI |
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- ▁SA |
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- ▁NA |
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- BIDE |
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- ▁KON |
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- ▁HE |
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- ▁ZUEN |
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- ▁MU |
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- ▁BESTE |
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- ▁SO |
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- ▁HERRI |
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- ▁IKAS |
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- ▁NO |
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- ▁ALD |
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- ▁NI |
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- ▁TX |
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- ABE |
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- KETA |
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- ▁BAINA |
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- C |
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- '!' |
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- V |
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- Y |
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- ':' |
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- ; |
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- '"' |
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- í |
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- Q |
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- ñ |
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- W |
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- J |
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- ‘ |
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- ’ |
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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: null |
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zero_infinity: true |
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joint_net_conf: null |
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use_preprocessor: true |
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token_type: bpe |
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bpemodel: data/eu_token_list/bpe_unigram150/bpe.model |
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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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short_noise_thres: 0.5 |
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aux_ctc_tasks: [] |
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frontend: default |
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frontend_conf: |
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n_fft: 512 |
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win_length: 400 |
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hop_length: 160 |
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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: global_mvn |
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normalize_conf: |
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stats_file: exp/asr_stats_raw_eu_bpe150_sp/train/feats_stats.npz |
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model: espnet |
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model_conf: |
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ctc_weight: 0.3 |
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lsm_weight: 0.1 |
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length_normalized_loss: false |
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preencoder: null |
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preencoder_conf: {} |
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encoder: conformer |
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encoder_conf: |
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input_layer: conv2d |
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num_blocks: 12 |
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linear_units: 2048 |
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dropout_rate: 0.1 |
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output_size: 256 |
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attention_heads: 4 |
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attention_dropout_rate: 0.0 |
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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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macaron_style: true |
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use_cnn_module: true |
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cnn_module_kernel: 15 |
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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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input_layer: embed |
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num_blocks: 6 |
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linear_units: 2048 |
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dropout_rate: 0.1 |
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preprocessor: default |
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preprocessor_conf: {} |
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required: |
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- output_dir |
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- token_list |
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version: '202308' |
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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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|
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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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