This model was trained by LiChenda using wsj0_2mix recipe in espnet. Python API See https://github.com/espnet/espnet_model_zoo Evaluate in the recipe git clone https://github.com/espnet/espnet cd espnet git checkout 08d2a6674adc536325ce15202c460ce9f5920f1b pip install -e . cd egs2/wsj0_2mix/enh1 ./run.sh --skip_data_prep false --skip_train true --download_model LiChenda/wsj0_2mix_enh_train_enh_dprnn_tasnet_raw_valid.si_snr.ave Results # RESULTS ## Environments - date: `Thu Apr 15 00:03:19 CST 2021` - python version: `3.7.10 (default, Feb 26 2021, 18:47:35) [GCC 7.3.0]` - espnet version: `espnet 0.9.8` - pytorch version: `pytorch 1.5.0` - Git hash: `2aa2f151b5929dc9ffa4df39a8d8c26ca4dbdb85` - Commit date: `Tue Mar 30 09:08:27 2021 +0900` ## enh_train_enh_dprnn_tasnet_raw config: conf/tuning/train_enh_dprnn_tasnet.yaml |dataset|STOI|SAR|SDR|SIR| |---|---|---|---|---| |enhanced_cv_min_8k|0.960037|19.0476|18.5438|29.1591| |enhanced_tt_min_8k|0.968376|18.8209|18.2925|28.929| ASR config config: conf/tuning/train_enh_dprnn_tasnet.yaml print_config: false log_level: INFO dry_run: false iterator_type: chunk output_dir: exp/enh_train_enh_dprnn_tasnet_raw ngpu: 1 seed: 0 num_workers: 4 num_att_plot: 3 dist_backend: nccl dist_init_method: env:// dist_world_size: 4 dist_rank: 0 local_rank: 0 dist_master_addr: localhost dist_master_port: 45126 dist_launcher: null multiprocessing_distributed: true unused_parameters: false sharded_ddp: false cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: true collect_stats: false write_collected_feats: false max_epoch: 150 patience: 4 val_scheduler_criterion: - valid - loss early_stopping_criterion: - valid - loss - min best_model_criterion: - - valid - si_snr - max - - valid - loss - min keep_nbest_models: 1 grad_clip: 5.0 grad_clip_type: 2.0 grad_noise: false accum_grad: 1 no_forward_run: false resume: true train_dtype: float32 use_amp: false log_interval: null use_tensorboard: true use_wandb: false wandb_project: null wandb_id: null detect_anomaly: false pretrain_path: null init_param: [] freeze_param: [] num_iters_per_epoch: null batch_size: 4 valid_batch_size: null batch_bins: 1000000 valid_batch_bins: null train_shape_file: - exp/enh_stats_8k/train/speech_mix_shape - exp/enh_stats_8k/train/speech_ref1_shape - exp/enh_stats_8k/train/speech_ref2_shape valid_shape_file: - exp/enh_stats_8k/valid/speech_mix_shape - exp/enh_stats_8k/valid/speech_ref1_shape - exp/enh_stats_8k/valid/speech_ref2_shape batch_type: folded valid_batch_type: null fold_length: - 80000 - 80000 - 80000 sort_in_batch: descending sort_batch: descending multiple_iterator: false chunk_length: 32000 chunk_shift_ratio: 0.5 num_cache_chunks: 1024 train_data_path_and_name_and_type: - - dump/raw/tr_min_8k/wav.scp - speech_mix - sound - - dump/raw/tr_min_8k/spk1.scp - speech_ref1 - sound - - dump/raw/tr_min_8k/spk2.scp - speech_ref2 - sound valid_data_path_and_name_and_type: - - dump/raw/cv_min_8k/wav.scp - speech_mix - sound - - dump/raw/cv_min_8k/spk1.scp - speech_ref1 - sound - - dump/raw/cv_min_8k/spk2.scp - speech_ref2 - sound allow_variable_data_keys: false max_cache_size: 0.0 max_cache_fd: 32 valid_max_cache_size: null optim: adam optim_conf: lr: 0.001 eps: 1.0e-08 weight_decay: 0 scheduler: reducelronplateau scheduler_conf: mode: min factor: 0.7 patience: 1 init: xavier_uniform model_conf: loss_type: si_snr use_preprocessor: false encoder: conv encoder_conf: channel: 64 kernel_size: 2 stride: 1 separator: dprnn separator_conf: num_spk: 2 layer: 6 rnn_type: lstm bidirectional: true nonlinear: relu unit: 128 segment_size: 250 dropout: 0.1 decoder: conv decoder_conf: channel: 64 kernel_size: 2 stride: 1 required: - output_dir version: 0.9.8 distributed: true