This model was trained by anogkongda using librimix 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 dcaba2585e28b85c815807165ba9953565ee8694 pip install -e . cd egs2/librimix/enh1 ./run.sh --skip_data_prep false --skip_train true --download_model anogkongda/librimix_enh_train_raw_valid.si_snr.ave Results # RESULTS ## Environments - date: `Mon Jan 25 19:16:45 CST 2021` - python version: `3.6.3 |Anaconda, Inc.| (default, Nov 20 2017, 20:41:42) [GCC 7.2.0]` - espnet version: `espnet 0.9.7` - pytorch version: `pytorch 1.6.0` - Git hash: `dcaba2585e28b85c815807165ba9953565ee8694` - Commit date: `Thu Jan 21 21:26:59 2021 +0800` ## enh_train_raw config: ./conf/train.yaml sample_rate: 8k min_or_max: min |dataset|STOI|SAR|SDR|SIR| |---|---|---|---|---| |enhanced_dev|0.845746|11.1029|10.6679|22.6471| |enhanced_test|0.846766|10.9166|10.4193|22.0783| ENH config config: ./conf/train.yaml print_config: false log_level: INFO dry_run: false iterator_type: chunk output_dir: exp/enh_train_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: 48369 dist_launcher: null multiprocessing_distributed: true cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: true collect_stats: false write_collected_feats: false max_epoch: 200 patience: 5 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 unused_parameters: false use_tensorboard: true use_wandb: false wandb_project: null wandb_id: null pretrain_path: null init_param: [] freeze_param: [] num_iters_per_epoch: null batch_size: 16 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 - exp/enh_stats_8k/train/noise_ref1_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 - exp/enh_stats_8k/valid/noise_ref1_shape batch_type: folded valid_batch_type: null fold_length: - 80000 - 80000 - 80000 - 80000 sort_in_batch: descending sort_batch: descending multiple_iterator: false chunk_length: 24000 chunk_shift_ratio: 0.5 num_cache_chunks: 1024 train_data_path_and_name_and_type: - - dump/raw/train/wav.scp - speech_mix - sound - - dump/raw/train/spk1.scp - speech_ref1 - sound - - dump/raw/train/spk2.scp - speech_ref2 - sound - - dump/raw/train/noise1.scp - noise_ref1 - sound valid_data_path_and_name_and_type: - - dump/raw/dev/wav.scp - speech_mix - sound - - dump/raw/dev/spk1.scp - speech_ref1 - sound - - dump/raw/dev/spk2.scp - speech_ref2 - sound - - dump/raw/dev/noise1.scp - noise_ref1 - 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 weight_decay: 0 scheduler: reducelronplateau scheduler_conf: mode: min factor: 0.5 patience: 1 init: xavier_uniform model_conf: loss_type: si_snr use_preprocessor: false encoder: conv encoder_conf: channel: 512 kernel_size: 16 stride: 8 separator: tcn separator_conf: num_spk: 2 layer: 8 stack: 3 bottleneck_dim: 128 hidden_dim: 512 kernel: 3 causal: false norm_type: gLN nonlinear: relu decoder: conv decoder_conf: channel: 512 kernel_size: 16 stride: 8 required: - output_dir version: 0.9.7 distributed: true