这个模型是由张旺友使用 chime4 的配方在 espnet 训练的。
cd espnet pip install -e . cd egs2/chime4/enh1 ./run.sh --skip_data_prep false --skip_train true --download_model espnet/Wangyou_Zhang_chime4_enh_train_enh_conv_tasnet_raw
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: 2 dist_rank: 0 local_rank: 0 dist_master_addr: localhost dist_master_port: 57680 dist_launcher: null multiprocessing_distributed: true 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_16k/train/speech_mix_shape - exp/enh_stats_16k/train/speech_ref1_shape valid_shape_file: - exp/enh_stats_16k/valid/speech_mix_shape - exp/enh_stats_16k/valid/speech_ref1_shape batch_type: folded valid_batch_type: null fold_length: - 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/tr05_simu_isolated_1ch_track/wav.scp - speech_mix - sound - - dump/raw/tr05_simu_isolated_1ch_track/spk1.scp - speech_ref1 - sound valid_data_path_and_name_and_type: - - dump/raw/dt05_simu_isolated_1ch_track/wav.scp - speech_mix - sound - - dump/raw/dt05_simu_isolated_1ch_track/spk1.scp - speech_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 eps: 1.0e-08 weight_decay: 1.0e-05 scheduler: reducelronplateau scheduler_conf: mode: min factor: 0.5 patience: 3 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: 1 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: true
@inproceedings{watanabe2018espnet, 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}, title={{ESPnet}: End-to-End Speech Processing Toolkit}, year={2018}, booktitle={Proceedings of Interspeech}, pages={2207--2211}, doi={10.21437/Interspeech.2018-1456}, url={http://dx.doi.org/10.21437/Interspeech.2018-1456} } @inproceedings{li2021espnetse, title={{ESPnet-SE}: End-to-End Speech Enhancement and Separation Toolkit Designed for {ASR} Integration}, author={Li, Chenda and Shi, Jing and Zhang, Wangyou and Subramanian, Aswin Shanmugam and Chang, Xuankai and Kamo, Naoyuki and Hira, Moto and Hayashi, Tomoki and Boeddeker, Christoph and Chen, Zhuo and Watanabe, Shinji}, booktitle={Proc. IEEE Spoken Language Technology Workshop (SLT)}, pages={785--792}, year={2021}, }
或 arXiv:
@misc{watanabe2018espnet, title={ESPnet: End-to-End Speech Processing Toolkit}, 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}, year={2018}, eprint={1804.00015}, archivePrefix={arXiv}, primaryClass={cs.CL} } @inproceedings{li2021espnetse, title={{ESPnet-SE}: End-to-End Speech Enhancement and Separation Toolkit Designed for {ASR} Integration}, author={Li, Chenda and Shi, Jing and Zhang, Wangyou and Subramanian, Aswin Shanmugam and Chang, Xuankai and Kamo, Naoyuki and Hira, Moto and Hayashi, Tomoki and Boeddeker, Christoph and Chen, Zhuo and Watanabe, Shinji}, year={2020}, eprint={2011.03706}, archivePrefix={arXiv}, primaryClass={eess.AS} }