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--- |
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tags: |
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- espnet |
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- audio |
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- diarization |
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language: en |
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datasets: |
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- librimix |
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license: cc-by-4.0 |
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--- |
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## ESPnet2 DIAR model |
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### `soumi-maiti/libri2mix_eend_ss` |
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This model was trained by soumimaiti using librimix 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 d837c97c88f13ffe655a30bcff93d814f212b225 |
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pip install -e . |
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cd egs2/librimix/enh_diar1 |
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./run.sh --skip_data_prep false --skip_train true --download_model soumi-maiti/libri2mix_eend_ss |
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``` |
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## DIAR config |
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<details><summary>expand</summary> |
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``` |
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config: conf/tuning/train_diar_enh_convtasnet_2.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: chunk |
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output_dir: exp/diar_enh_train_diar_enh_convtasnet_2_raw |
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ngpu: 1 |
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seed: 0 |
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num_workers: 4 |
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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: 55259 |
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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: 100 |
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patience: 4 |
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val_scheduler_criterion: |
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- valid |
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- loss |
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early_stopping_criterion: |
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- valid |
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- loss |
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- min |
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best_model_criterion: |
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- - valid |
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- loss_enh |
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- min |
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keep_nbest_models: 1 |
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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: 16 |
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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/diar_enh_stats_8k/train/speech_shape |
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- exp/diar_enh_stats_8k/train/text_shape |
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- exp/diar_enh_stats_8k/train/speech_ref1_shape |
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- exp/diar_enh_stats_8k/train/speech_ref2_shape |
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- exp/diar_enh_stats_8k/train/noise_ref1_shape |
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valid_shape_file: |
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- exp/diar_enh_stats_8k/valid/speech_shape |
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- exp/diar_enh_stats_8k/valid/text_shape |
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- exp/diar_enh_stats_8k/valid/speech_ref1_shape |
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- exp/diar_enh_stats_8k/valid/speech_ref2_shape |
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- exp/diar_enh_stats_8k/valid/noise_ref1_shape |
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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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- 80000 |
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- 80000 |
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- 80000 |
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- 80000 |
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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: 24000 |
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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/wav.scp |
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- speech |
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- sound |
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- - dump/raw/train/espnet_rttm |
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- text |
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- rttm |
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- - dump/raw/train/spk1.scp |
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- speech_ref1 |
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- sound |
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- - dump/raw/train/spk2.scp |
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- speech_ref2 |
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- sound |
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- - dump/raw/train/noise1.scp |
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- noise_ref1 |
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- sound |
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valid_data_path_and_name_and_type: |
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- - dump/raw/dev/wav.scp |
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- speech |
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- sound |
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- - dump/raw/dev/espnet_rttm |
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- text |
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- rttm |
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- - dump/raw/dev/spk1.scp |
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- speech_ref1 |
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- sound |
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- - dump/raw/dev/spk2.scp |
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- speech_ref2 |
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- sound |
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- - dump/raw/dev/noise1.scp |
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- noise_ref1 |
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- sound |
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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: 0.001 |
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eps: 1.0e-07 |
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weight_decay: 0 |
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scheduler: reducelronplateau |
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scheduler_conf: |
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mode: min |
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factor: 0.5 |
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patience: 1 |
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token_list: null |
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src_token_list: null |
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init: xavier_uniform |
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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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enh_criterions: |
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- name: si_snr |
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conf: |
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eps: 1.0e-07 |
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wrapper: pit |
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wrapper_conf: |
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weight: 1.0 |
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independent_perm: true |
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diar_num_spk: 2 |
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diar_input_size: 128 |
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enh_model_conf: |
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loss_type: si_snr |
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asr_model_conf: |
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ctc_weight: 0.5 |
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interctc_weight: 0.0 |
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ignore_id: -1 |
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lsm_weight: 0.0 |
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length_normalized_loss: false |
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report_cer: true |
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report_wer: true |
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sym_space: <space> |
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sym_blank: <blank> |
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extract_feats_in_collect_stats: true |
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st_model_conf: |
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stft_consistency: false |
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loss_type: mask_mse |
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mask_type: null |
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diar_model_conf: |
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diar_weight: 0.2 |
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attractor_weight: 0.2 |
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subtask_series: |
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- enh |
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- diar |
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model_conf: |
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calc_enh_loss: true |
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bypass_enh_prob: 0 |
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use_preprocessor: true |
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token_type: bpe |
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bpemodel: null |
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src_token_type: bpe |
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src_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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enh_encoder: conv |
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enh_encoder_conf: |
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channel: 512 |
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kernel_size: 16 |
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stride: 8 |
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enh_separator: tcn_nomask |
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enh_separator_conf: |
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layer: 8 |
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stack: 3 |
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bottleneck_dim: 128 |
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hidden_dim: 512 |
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kernel: 3 |
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causal: false |
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norm_type: gLN |
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enh_decoder: conv |
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enh_decoder_conf: |
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channel: 512 |
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kernel_size: 16 |
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stride: 8 |
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enh_mask_module: multi_mask |
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enh_mask_module_conf: |
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max_num_spk: 3 |
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mask_nonlinear: relu |
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bottleneck_dim: 128 |
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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: utterance_mvn |
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normalize_conf: {} |
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asr_preencoder: null |
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asr_preencoder_conf: {} |
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asr_encoder: rnn |
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asr_encoder_conf: {} |
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asr_postencoder: null |
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asr_postencoder_conf: {} |
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asr_decoder: rnn |
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asr_decoder_conf: {} |
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st_preencoder: null |
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st_preencoder_conf: {} |
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st_encoder: rnn |
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st_encoder_conf: {} |
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st_postencoder: null |
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st_postencoder_conf: {} |
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st_decoder: rnn |
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st_decoder_conf: {} |
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st_extra_asr_decoder: rnn |
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st_extra_asr_decoder_conf: {} |
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st_extra_mt_decoder: rnn |
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st_extra_mt_decoder_conf: {} |
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diar_frontend: null |
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diar_frontend_conf: {} |
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diar_specaug: null |
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diar_specaug_conf: {} |
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diar_normalize: utterance_mvn |
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diar_normalize_conf: {} |
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diar_encoder: transformer |
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diar_encoder_conf: |
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input_layer: conv2d8 |
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num_blocks: 4 |
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linear_units: 512 |
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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: 0.1 |
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diar_decoder: linear |
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diar_decoder_conf: {} |
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label_aggregator: label_aggregator |
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label_aggregator_conf: |
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win_length: 256 |
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hop_length: 64 |
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diar_attractor: rnn |
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diar_attractor_conf: |
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unit: 256 |
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layer: 1 |
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dropout: 0.0 |
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attractor_grad: true |
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required: |
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- output_dir |
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version: '202205' |
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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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