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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: pt |
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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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## ESPnet2 ASR model |
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### `espnet/pt_commonvoice_blstm` |
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This model was trained by dzeinali using commonvoice 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 716eb8f92e19708acfd08ba3bd39d40890d3a84b |
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pip install -e . |
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cd egs2/commonvoice/asr1 |
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./run.sh --skip_data_prep false --skip_train true --download_model espnet/pt_commonvoice_blstm |
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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 Apr 11 18:55:23 EDT 2022` |
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- python version: `3.9.5 (default, Jun 4 2021, 12:28:51) [GCC 7.5.0]` |
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- espnet version: `espnet 0.10.6a1` |
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- pytorch version: `pytorch 1.8.1+cu102` |
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- Git hash: `5e6e95d087af8a7a4c33c4248b75114237eae64b` |
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- Commit date: `Mon Apr 4 21:04:45 2022 -0400` |
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## asr_train_asr_rnn_raw_pt_bpe150_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_rnn_asr_model_valid.acc.best/test_pt|4334|33716|84.7|12.4|2.9|1.3|16.6|46.8| |
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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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|decode_rnn_asr_model_valid.acc.best/test_pt|4334|191499|93.4|3.0|3.6|1.2|7.8|46.9| |
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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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|decode_rnn_asr_model_valid.acc.best/test_pt|4334|116003|90.4|5.7|3.9|1.5|11.1|46.9| |
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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_rnn.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_rnn_raw_pt_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: 15 |
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patience: 3 |
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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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- - train |
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- loss |
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- min |
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- - valid |
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- loss |
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- min |
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- - train |
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- acc |
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- max |
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- - valid |
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- acc |
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- max |
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keep_nbest_models: |
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- 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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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: 30 |
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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_raw_pt_bpe150_sp/train/speech_shape |
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- exp/asr_stats_raw_pt_bpe150_sp/train/text_shape.bpe |
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valid_shape_file: |
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- exp/asr_stats_raw_pt_bpe150_sp/valid/speech_shape |
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- exp/asr_stats_raw_pt_bpe150_sp/valid/text_shape.bpe |
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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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- 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_pt_sp/wav.scp |
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- speech |
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- sound |
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- - dump/raw/train_pt_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_pt/wav.scp |
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- speech |
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- sound |
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- - dump/raw/dev_pt/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: adadelta |
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optim_conf: |
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lr: 0.1 |
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scheduler: null |
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scheduler_conf: {} |
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token_list: |
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- <blank> |
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- <unk> |
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- ▁ |
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- S |
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- R |
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- I |
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- U |
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- E |
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- O |
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- A |
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- . |
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- N |
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- M |
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- L |
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- ▁A |
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- ▁DE |
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- RA |
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- ▁O |
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- T |
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- ▁E |
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- ▁UM |
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- C |
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- TA |
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- DO |
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- G |
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- TO |
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- TE |
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- DA |
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- VE |
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- B |
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- NDO |
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- ▁SE |
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- ▁QUE |
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- P |
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- ▁UMA |
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- LA |
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- D |
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- ▁COM |
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- CA |
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- á |
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- '?' |
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- ▁PE |
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- ▁EM |
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- IN |
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- TI |
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- IS |
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- ▁C |
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- H |
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- HO |
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- ▁CA |
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- ▁P |
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- CO |
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- ',' |
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- ▁NO |
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- MA |
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- NTE |
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- PA |
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- ▁NãO |
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- DE |
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- ãO |
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- ▁ME |
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- ▁PARA |
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- Z |
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- ▁MA |
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- VA |
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- PO |
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- ▁DO |
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- ▁VOCê |
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- RI |
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- ▁DI |
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- GA |
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- VI |
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- ▁é |
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- LO |
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- IA |
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- ▁ELE |
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- ▁EU |
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- ▁ESTá |
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- HA |
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- ▁M |
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- X |
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- ▁NA |
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- NA |
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- é |
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- CE |
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- LE |
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- GO |
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- VO |
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- ▁RE |
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- ▁FO |
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- ▁FA |
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- ▁CO |
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- QUE |
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- ▁EST |
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- BE |
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- ▁CON |
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- ó |
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- SE |
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- ▁POR |
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- ê |
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- í |
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- çãO |
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- ▁DA |
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- RES |
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- ▁QUA |
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- ▁HOMEM |
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- RIA |
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- çA |
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- ▁SA |
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- V |
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- ▁PRE |
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- MENTE |
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- ZE |
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- NHA |
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- '-' |
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- ▁BA |
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- MOS |
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- ▁SO |
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- ▁BO |
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- ç |
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- '"' |
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- '!' |
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- ú |
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- ã |
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- K |
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- Y |
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- É |
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- W |
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- ô |
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- Á |
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- ':' |
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- ; |
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- '''' |
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- ” |
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- Ô |
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- ñ |
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- “ |
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- Ú |
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- Í |
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- Ó |
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- ü |
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- À |
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- â |
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- à |
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- õ |
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- J |
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- Q |
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- F |
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- Â |
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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: 0.5 |
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use_preprocessor: true |
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token_type: bpe |
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bpemodel: data/pt_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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frontend: default |
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frontend_conf: |
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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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- 27 |
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num_freq_mask: 2 |
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apply_time_mask: true |
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time_mask_width_ratio_range: |
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- 0.0 |
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- 0.05 |
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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_pt_bpe150_sp/train/feats_stats.npz |
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preencoder: null |
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preencoder_conf: {} |
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encoder: vgg_rnn |
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encoder_conf: |
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rnn_type: lstm |
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bidirectional: true |
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use_projection: true |
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num_layers: 4 |
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hidden_size: 1024 |
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output_size: 1024 |
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postencoder: null |
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postencoder_conf: {} |
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decoder: rnn |
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decoder_conf: |
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num_layers: 2 |
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hidden_size: 1024 |
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sampling_probability: 0 |
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att_conf: |
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atype: location |
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adim: 1024 |
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aconv_chans: 10 |
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aconv_filts: 100 |
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required: |
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- output_dir |
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- token_list |
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version: 0.10.6a1 |
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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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