ESPnet2 pretrained model, Chenda Li/wsj0_2mix_enh_train_enh_conv_tasnet_raw_valid.si_snr.ave, fs=8k, lang=en
Creators: name: Chenda Li
Publisher: name: Zenodo
Year: 2021
Subjects: ESPnet
deep-learning
python
pytorch
speech-separation
speech-recognition
speech-synthesis
speech-translation
machine-translation

description: This model was trained by Chenda Li using wsj0_2mix recipe in espnet. <strong>Python API</strong> <pre><code class="language-python">See https://github.com/espnet/espnet_model_zoo</code></pre> <strong>Evaluate in the recipe</strong> <pre><code class="language-bash">git clone https://github.com/espnet/espnet cd espnet git checkout a3334220b0352931677946d178fade3313cf82bb pip install -e . cd egs2/wsj0_2mix/enh1 ./run.sh --skip_data_prep false --skip_train true --download_model Chenda Li/wsj0_2mix_enh_train_enh_conv_tasnet_raw_valid.si_snr.ave</code> </pre> <strong>Results</strong> <pre><code> # RESULTS ## Environments - date: `Thu Feb 4 01:16:18 CST 2021` - python version: `3.7.6 (default, Jan 8 2020, 19:59:22) [GCC 7.3.0]` - espnet version: `espnet 0.9.7` - pytorch version: `pytorch 1.5.0` - Git hash: `a3334220b0352931677946d178fade3313cf82bb` - Commit date: `Fri Jan 29 23:35:47 2021 +0800` ## enh_train_enh_conv_tasnet_raw config: ./conf/tuning/train_enh_conv_tasnet.yaml |dataset|STOI|SAR|SDR|SIR| |---|---|---|---|---| |enhanced_cv_min_8k|0.949205|17.3785|16.8028|26.9785| |enhanced_tt_min_8k|0.95349|16.6221|15.9494|25.9032|</code></pre> <strong>ASR config</strong> <pre><code>config: ./conf/tuning/train_enh_conv_tasnet.yaml print_config: false log_level: INFO dry_run: false iterator_type: chunk output_dir: exp/enh_train_enh_conv_tasnet_raw ngpu: 1 seed: 0 num_workers: 4 num_att_plot: 3 dist_backend: nccl dist_init_method: env:// dist_world_size: null dist_rank: null local_rank: 0 dist_master_addr: null dist_master_port: null dist_launcher: null multiprocessing_distributed: false cudnn_enabled: true cudnn_benchmark: false cudnn_deterministic: true collect_stats: false write_collected_feats: false max_epoch: 100 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 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: 8 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: 0.5 patience: 1 init: xavier_uniform model_conf: loss_type: si_snr use_preprocessor: false encoder: conv encoder_conf: channel: 256 kernel_size: 20 stride: 10 separator: tcn separator_conf: num_spk: 2 layer: 8 stack: 4 bottleneck_dim: 256 hidden_dim: 512 kernel: 3 causal: false norm_type: gLN nonlinear: relu decoder: conv decoder_conf: channel: 256 kernel_size: 20 stride: 10 required: - output_dir version: 0.9.7 distributed: false</code></pre>