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--- |
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tags: |
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- espnet |
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- image-to-text |
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- ocr |
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- handwriting-recognition |
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language: en |
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datasets: |
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- iam |
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license: cc-by-4.0 |
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--- |
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## ESPnet2 ASR model |
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### `espnet/iam_handwriting_ocr` |
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This model was trained by kenzheng99 using iam 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 2169367022b8939d22005e8cf45a65bb20bc0768 |
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pip install -e . |
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cd egs2/iam/ocr1 |
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./run.sh --skip_data_prep false --skip_train true --download_model espnet/iam_handwriting_ocr |
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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: `Mon Nov 7 13:40:17 EST 2022` |
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- python version: `3.7.13 (default, Mar 29 2022, 02:18:16) [GCC 7.5.0]` |
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- espnet version: `espnet 202209` |
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- pytorch version: `pytorch 1.10.0` |
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- Git hash: `2169367022b8939d22005e8cf45a65bb20bc0768` |
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- Commit date: `Thu Nov 3 20:38:03 2022 -0400` |
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## asr_train_asr_conformer_extracted_en_char |
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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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|inference_asr_model_valid.acc.ave/test|2915|25932|80.5|17.3|2.2|0.8|20.3|72.8| |
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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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|inference_asr_model_valid.acc.ave/test|2915|125616|94.0|4.2|1.8|0.7|6.7|72.8| |
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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/train_asr_conformer.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_extracted_en_char |
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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: 4 |
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dist_rank: 0 |
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local_rank: 0 |
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dist_master_addr: localhost |
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dist_master_port: 35197 |
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dist_launcher: null |
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multiprocessing_distributed: true |
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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: 200 |
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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: 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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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: 64 |
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valid_batch_size: null |
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batch_bins: 1000000 |
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valid_batch_bins: null |
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train_shape_file: |
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- exp/asr_stats_extracted_en_char/train/speech_shape |
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- exp/asr_stats_extracted_en_char/train/text_shape.char |
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valid_shape_file: |
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- exp/asr_stats_extracted_en_char/valid/speech_shape |
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- exp/asr_stats_extracted_en_char/valid/text_shape.char |
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batch_type: folded |
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valid_batch_type: null |
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fold_length: |
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- 800 |
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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/extracted/train/feats.scp |
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- speech |
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- kaldi_ark |
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- - dump/extracted/train/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/extracted/valid/feats.scp |
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- speech |
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- kaldi_ark |
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- - dump/extracted/valid/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: 0.002 |
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weight_decay: 1.0e-06 |
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scheduler: warmuplr |
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scheduler_conf: |
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warmup_steps: 15000 |
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token_list: |
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- <blank> |
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- <unk> |
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- <space> |
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- e |
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- t |
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- a |
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- o |
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- n |
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- i |
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- r |
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- s |
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- h |
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- l |
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- d |
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- c |
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- u |
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- m |
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- f |
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- p |
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- g |
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- y |
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- w |
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- b |
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- . |
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- ',' |
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- v |
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- k |
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- '-' |
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- T |
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- '''' |
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- M |
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- I |
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- A |
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- '"' |
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- S |
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- P |
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- H |
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- B |
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- C |
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- W |
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- N |
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- G |
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- x |
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- R |
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- E |
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- L |
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- F |
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- '0' |
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- D |
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- '1' |
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- j |
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- O |
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- q |
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- U |
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- K |
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- '!' |
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- '3' |
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- '9' |
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- ( |
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- z |
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- ) |
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- ':' |
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- V |
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- ; |
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- '5' |
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- '2' |
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- J |
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- '8' |
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- Y |
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- '4' |
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- '6' |
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- '?' |
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- '#' |
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- '&' |
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- '7' |
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- / |
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- '*' |
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- Q |
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- X |
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- Z |
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- + |
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- <sos/eos> |
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init: xavier_uniform |
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input_size: 100 |
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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: char |
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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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short_noise_thres: 0.5 |
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frontend: null |
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frontend_conf: {} |
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specaug: null |
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specaug_conf: {} |
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normalize: global_mvn |
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normalize_conf: |
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stats_file: exp/asr_stats_extracted_en_char/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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output_size: 256 |
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attention_heads: 4 |
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linear_units: 1024 |
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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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rel_pos_type: latest |
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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: 4 |
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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: '202209' |
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distributed: true |
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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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