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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: fa |
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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/farsi_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/farsi_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 May 2 11:48:56 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: `716eb8f92e19708acfd08ba3bd39d40890d3a84b` |
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- Commit date: `Thu Apr 28 19:50:59 2022 -0400` |
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## asr_train_asr_rnn_raw_fa_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.ave/test_fa|9728|68904|0.0|0.0|100.0|0.0|100.0|100.0| |
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|decode_rnn_asr_model_valid.acc.best/test_fa|9728|68904|91.4|7.2|1.4|1.0|9.5|30.1| |
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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.ave/test_fa|9728|331506|0.0|0.0|100.0|0.0|100.0|100.0| |
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|decode_rnn_asr_model_valid.acc.best/test_fa|9728|331506|97.2|1.3|1.5|0.7|3.6|30.1| |
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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.ave/test_fa|9728|230963|0.0|0.0|100.0|0.0|100.0|100.0| |
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|decode_rnn_asr_model_valid.acc.best/test_fa|9728|230963|95.9|2.4|1.6|0.7|4.7|30.1| |
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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_fa_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_fa_bpe150_sp/train/speech_shape |
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- exp/asr_stats_raw_fa_bpe150_sp/train/text_shape.bpe |
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valid_shape_file: |
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- exp/asr_stats_raw_fa_bpe150_sp/valid/speech_shape |
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- exp/asr_stats_raw_fa_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_fa_sp/wav.scp |
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- speech |
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- sound |
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- - dump/raw/train_fa_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_fa/wav.scp |
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- speech |
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- sound |
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- - dump/raw/dev_fa/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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- ی |
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- ا |
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- ه |
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- ▁ |
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- ر |
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- م |
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- و |
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- د |
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- ت |
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- ش |
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- ن |
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- ل |
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- ▁ب |
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- ز |
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- ب |
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- . |
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- ▁م |
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- ان |
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- ▁ا |
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- س |
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- ک |
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- ▁می |
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- گ |
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- ف |
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- ▁د |
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- ؟ |
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- ق |
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- ▁و |
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- ید |
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- ▁ن |
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- ند |
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- ست |
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- ار |
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- ▁چ |
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- ع |
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- ج |
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- ▁ت |
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- ▁ک |
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- ▁با |
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- خ |
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- ون |
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- ▁پ |
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- ▁به |
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- ▁من |
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- ▁س |
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- ▁را |
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- ، |
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- ▁خ |
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- ▁این |
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- ▁کن |
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- ▁آ |
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- ▁در |
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- ای |
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- ▁از |
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- اد |
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- ▁است |
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- ح |
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- ص |
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- ▁ش |
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- ط |
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- ▁تو |
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- ین |
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- ▁دار |
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- ▁که |
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- ال |
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- ▁رو |
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- ▁گ |
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- ▁ج |
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- ور |
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- ام |
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- ▁هم |
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- ▁ح |
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- فت |
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- رد |
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- یم |
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- پ |
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- غ |
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- چ |
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- ذ |
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- ض |
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- ظ |
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- '!' |
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- ث |
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- ً |
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- ئ |
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- '"' |
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- ژ |
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- ك |
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- آ |
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- ي |
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- ':' |
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- ى |
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- '-' |
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- ِ |
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- أ |
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- َ |
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- » |
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- ـ |
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- ',' |
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- ُ |
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- ( |
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- ) |
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- ء |
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- ٔ |
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- ٬ |
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- ّ |
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- ؛ |
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- B |
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- C |
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- A |
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- E |
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- G |
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- M |
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- S |
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- ؤ |
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- I |
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- ; |
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- T |
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- H |
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- _ |
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- F |
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- D |
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- ۀ |
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- Y |
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- N |
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- K |
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- U |
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- – |
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- ٌ |
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- P |
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- O |
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- Q |
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- Z |
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- '&' |
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- L |
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- R |
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- ة |
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- X |
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- ā |
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- '#' |
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- “ |
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- '=' |
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- « |
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- š |
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- ْ |
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- ے |
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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: 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/fa_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_fa_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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