Update model
Browse files- README.md +233 -0
- exp/diar_stats_8k/train/feats_stats.npz +0 -0
- exp/diar_train_diar_eda_adapt_simu/13epoch.pth +3 -0
- exp/diar_train_diar_eda_adapt_simu/RESULTS.md +0 -0
- exp/diar_train_diar_eda_adapt_simu/config.yaml +163 -0
- exp/diar_train_diar_eda_adapt_simu/images/acc.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/backward_time.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/cf.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/der.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/fa.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/forward_time.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/gpu_max_cached_mem_GB.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/iter_time.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/loss.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/loss_att.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/loss_pit.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/mi.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/optim0_lr0.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/optim_step_time.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/sad_fr.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/sad_mr.png +0 -0
- exp/diar_train_diar_eda_adapt_simu/images/train_time.png +0 -0
- meta.yaml +8 -0
README.md
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1 |
+
---
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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: noinfo
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datasets:
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- callhome
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license: cc-by-4.0
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+
---
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## ESPnet2 DIAR model
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+
### `YushiUeda/callhome_adapt_simu`
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This model was trained by YushiUeda using callhome 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 0cabe65afd362122e77b04e2e967986a91de0fd8
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pip install -e .
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cd egs2/callhome/diar1
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./run.sh --skip_data_prep false --skip_train true --download_model YushiUeda/callhome_adapt_simu
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```
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+
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+
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## DIAR config
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+
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<details><summary>expand</summary>
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+
|
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```
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config: conf/tuning/train_diar_eda_adapt.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/diar_train_diar_eda_adapt_simu
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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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46 |
+
dist_init_method: env://
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47 |
+
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: 43777
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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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60 |
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write_collected_feats: false
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61 |
+
max_epoch: 50
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patience: null
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val_scheduler_criterion:
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- valid
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65 |
+
- loss
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66 |
+
early_stopping_criterion:
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67 |
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- valid
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68 |
+
- loss
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- min
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+
best_model_criterion:
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- - valid
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72 |
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- acc
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- max
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- - train
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- acc
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- max
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keep_nbest_models: 10
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78 |
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nbest_averaging_interval: 0
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79 |
+
grad_clip: 5
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+
grad_clip_type: 2.0
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81 |
+
grad_noise: false
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82 |
+
accum_grad: 4
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no_forward_run: false
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84 |
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resume: true
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train_dtype: float32
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use_amp: false
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87 |
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log_interval: null
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88 |
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use_matplotlib: true
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use_tensorboard: true
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90 |
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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:
|
99 |
+
- exp/diar_train_diar_eda_5_raw/latest.pth
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ignore_init_mismatch: false
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101 |
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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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108 |
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- exp/diar_stats_8k/train/speech_shape
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- exp/diar_stats_8k/train/spk_labels_shape
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valid_shape_file:
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- exp/diar_stats_8k/valid/speech_shape
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- exp/diar_stats_8k/valid/spk_labels_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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- 80000
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- 800
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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/simu/data/swb_sre_tr_ns1n2n3n4_beta2n2n5n9_100000/wav.scp
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- speech
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- sound
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- - dump/raw/simu/data/swb_sre_tr_ns1n2n3n4_beta2n2n5n9_100000/espnet_rttm
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- spk_labels
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- rttm
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valid_data_path_and_name_and_type:
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- - dump/raw/simu/data/swb_sre_cv_ns1n2n3n4_beta2n2n5n9_500/wav.scp
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- speech
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- sound
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- - dump/raw/simu/data/swb_sre_cv_ns1n2n3n4_beta2n2n5n9_500/espnet_rttm
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- spk_labels
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- rttm
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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: 0.0001
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scheduler: null
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scheduler_conf: {}
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num_spk: 4
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+
init: null
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input_size: null
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+
model_conf:
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+
attractor_weight: 1.0
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+
use_preprocessor: true
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153 |
+
frontend: default
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+
frontend_conf:
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155 |
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fs: 8k
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+
hop_length: 128
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+
specaug: specaug
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specaug_conf:
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+
apply_time_warp: false
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+
apply_freq_mask: true
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+
freq_mask_width_range:
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- 0
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- 30
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num_freq_mask: 2
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+
apply_time_mask: true
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+
time_mask_width_range:
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+
- 0
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+
- 40
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+
num_time_mask: 2
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+
normalize: global_mvn
|
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+
normalize_conf:
|
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+
stats_file: exp/diar_stats_8k/train/feats_stats.npz
|
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+
encoder: transformer
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+
encoder_conf:
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input_layer: conv2d
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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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+
decoder: linear
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+
decoder_conf: {}
|
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+
label_aggregator: label_aggregator
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label_aggregator_conf:
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+
win_length: 1024
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+
hop_length: 512
|
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+
attractor: rnn
|
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+
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: '202204'
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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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|
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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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213 |
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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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|
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```
|
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or arXiv:
|
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|
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```bibtex
|
225 |
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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},
|
229 |
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eprint={1804.00015},
|
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archivePrefix={arXiv},
|
231 |
+
primaryClass={cs.CL}
|
232 |
+
}
|
233 |
+
```
|
exp/diar_stats_8k/train/feats_stats.npz
ADDED
Binary file (1.4 kB). View file
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exp/diar_train_diar_eda_adapt_simu/13epoch.pth
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:006735290e86e1ee4bb46dc5abaa7f62ffe4c86da385fc3560407ee45dda4e04
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size 20113016
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exp/diar_train_diar_eda_adapt_simu/RESULTS.md
ADDED
File without changes
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exp/diar_train_diar_eda_adapt_simu/config.yaml
ADDED
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config: conf/tuning/train_diar_eda_adapt.yaml
|
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print_config: false
|
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+
log_level: INFO
|
4 |
+
dry_run: false
|
5 |
+
iterator_type: sequence
|
6 |
+
output_dir: exp/diar_train_diar_eda_adapt_simu
|
7 |
+
ngpu: 1
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seed: 0
|
9 |
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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: 43777
|
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dist_launcher: null
|
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multiprocessing_distributed: true
|
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unused_parameters: false
|
21 |
+
sharded_ddp: false
|
22 |
+
cudnn_enabled: true
|
23 |
+
cudnn_benchmark: false
|
24 |
+
cudnn_deterministic: true
|
25 |
+
collect_stats: false
|
26 |
+
write_collected_feats: false
|
27 |
+
max_epoch: 50
|
28 |
+
patience: null
|
29 |
+
val_scheduler_criterion:
|
30 |
+
- valid
|
31 |
+
- loss
|
32 |
+
early_stopping_criterion:
|
33 |
+
- valid
|
34 |
+
- loss
|
35 |
+
- min
|
36 |
+
best_model_criterion:
|
37 |
+
- - valid
|
38 |
+
- acc
|
39 |
+
- max
|
40 |
+
- - train
|
41 |
+
- acc
|
42 |
+
- max
|
43 |
+
keep_nbest_models: 10
|
44 |
+
nbest_averaging_interval: 0
|
45 |
+
grad_clip: 5
|
46 |
+
grad_clip_type: 2.0
|
47 |
+
grad_noise: false
|
48 |
+
accum_grad: 4
|
49 |
+
no_forward_run: false
|
50 |
+
resume: true
|
51 |
+
train_dtype: float32
|
52 |
+
use_amp: false
|
53 |
+
log_interval: null
|
54 |
+
use_matplotlib: true
|
55 |
+
use_tensorboard: true
|
56 |
+
use_wandb: false
|
57 |
+
wandb_project: null
|
58 |
+
wandb_id: null
|
59 |
+
wandb_entity: null
|
60 |
+
wandb_name: null
|
61 |
+
wandb_model_log_interval: -1
|
62 |
+
detect_anomaly: false
|
63 |
+
pretrain_path: null
|
64 |
+
init_param:
|
65 |
+
- exp/diar_train_diar_eda_5_raw/latest.pth
|
66 |
+
ignore_init_mismatch: false
|
67 |
+
freeze_param: []
|
68 |
+
num_iters_per_epoch: null
|
69 |
+
batch_size: 16
|
70 |
+
valid_batch_size: null
|
71 |
+
batch_bins: 1000000
|
72 |
+
valid_batch_bins: null
|
73 |
+
train_shape_file:
|
74 |
+
- exp/diar_stats_8k/train/speech_shape
|
75 |
+
- exp/diar_stats_8k/train/spk_labels_shape
|
76 |
+
valid_shape_file:
|
77 |
+
- exp/diar_stats_8k/valid/speech_shape
|
78 |
+
- exp/diar_stats_8k/valid/spk_labels_shape
|
79 |
+
batch_type: folded
|
80 |
+
valid_batch_type: null
|
81 |
+
fold_length:
|
82 |
+
- 80000
|
83 |
+
- 800
|
84 |
+
sort_in_batch: descending
|
85 |
+
sort_batch: descending
|
86 |
+
multiple_iterator: false
|
87 |
+
chunk_length: 500
|
88 |
+
chunk_shift_ratio: 0.5
|
89 |
+
num_cache_chunks: 1024
|
90 |
+
train_data_path_and_name_and_type:
|
91 |
+
- - dump/raw/simu/data/swb_sre_tr_ns1n2n3n4_beta2n2n5n9_100000/wav.scp
|
92 |
+
- speech
|
93 |
+
- sound
|
94 |
+
- - dump/raw/simu/data/swb_sre_tr_ns1n2n3n4_beta2n2n5n9_100000/espnet_rttm
|
95 |
+
- spk_labels
|
96 |
+
- rttm
|
97 |
+
valid_data_path_and_name_and_type:
|
98 |
+
- - dump/raw/simu/data/swb_sre_cv_ns1n2n3n4_beta2n2n5n9_500/wav.scp
|
99 |
+
- speech
|
100 |
+
- sound
|
101 |
+
- - dump/raw/simu/data/swb_sre_cv_ns1n2n3n4_beta2n2n5n9_500/espnet_rttm
|
102 |
+
- spk_labels
|
103 |
+
- rttm
|
104 |
+
allow_variable_data_keys: false
|
105 |
+
max_cache_size: 0.0
|
106 |
+
max_cache_fd: 32
|
107 |
+
valid_max_cache_size: null
|
108 |
+
optim: adam
|
109 |
+
optim_conf:
|
110 |
+
lr: 0.0001
|
111 |
+
scheduler: null
|
112 |
+
scheduler_conf: {}
|
113 |
+
num_spk: 4
|
114 |
+
init: null
|
115 |
+
input_size: null
|
116 |
+
model_conf:
|
117 |
+
attractor_weight: 1.0
|
118 |
+
use_preprocessor: true
|
119 |
+
frontend: default
|
120 |
+
frontend_conf:
|
121 |
+
fs: 8k
|
122 |
+
hop_length: 128
|
123 |
+
specaug: specaug
|
124 |
+
specaug_conf:
|
125 |
+
apply_time_warp: false
|
126 |
+
apply_freq_mask: true
|
127 |
+
freq_mask_width_range:
|
128 |
+
- 0
|
129 |
+
- 30
|
130 |
+
num_freq_mask: 2
|
131 |
+
apply_time_mask: true
|
132 |
+
time_mask_width_range:
|
133 |
+
- 0
|
134 |
+
- 40
|
135 |
+
num_time_mask: 2
|
136 |
+
normalize: global_mvn
|
137 |
+
normalize_conf:
|
138 |
+
stats_file: exp/diar_stats_8k/train/feats_stats.npz
|
139 |
+
encoder: transformer
|
140 |
+
encoder_conf:
|
141 |
+
input_layer: conv2d
|
142 |
+
num_blocks: 4
|
143 |
+
linear_units: 512
|
144 |
+
dropout_rate: 0.1
|
145 |
+
output_size: 256
|
146 |
+
attention_heads: 4
|
147 |
+
attention_dropout_rate: 0.1
|
148 |
+
decoder: linear
|
149 |
+
decoder_conf: {}
|
150 |
+
label_aggregator: label_aggregator
|
151 |
+
label_aggregator_conf:
|
152 |
+
win_length: 1024
|
153 |
+
hop_length: 512
|
154 |
+
attractor: rnn
|
155 |
+
attractor_conf:
|
156 |
+
unit: 256
|
157 |
+
layer: 1
|
158 |
+
dropout: 0.0
|
159 |
+
attractor_grad: true
|
160 |
+
required:
|
161 |
+
- output_dir
|
162 |
+
version: '202204'
|
163 |
+
distributed: true
|
exp/diar_train_diar_eda_adapt_simu/images/acc.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/backward_time.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/cf.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/der.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/fa.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/forward_time.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/gpu_max_cached_mem_GB.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/iter_time.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/loss.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/loss_att.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/loss_pit.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/mi.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/optim0_lr0.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/optim_step_time.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/sad_fr.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/sad_mr.png
ADDED
exp/diar_train_diar_eda_adapt_simu/images/train_time.png
ADDED
meta.yaml
ADDED
@@ -0,0 +1,8 @@
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|
|
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|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
espnet: '202205'
|
2 |
+
files:
|
3 |
+
model_file: exp/diar_train_diar_eda_adapt_simu/13epoch.pth
|
4 |
+
python: "3.7.11 (default, Jul 27 2021, 14:32:16) \n[GCC 7.5.0]"
|
5 |
+
timestamp: 1656444101.362689
|
6 |
+
torch: 1.9.1+cu102
|
7 |
+
yaml_files:
|
8 |
+
train_config: exp/diar_train_diar_eda_adapt_simu/config.yaml
|