模型:
mpariente/ConvTasNet_WHAM_sepclean
任务:
音频到音频许可:
cc-by-sa-4.0从 Zenodo 导入
该模型是由Manuel Pariente使用wham/ConvTasNet配方在 Asteroid 上训练的。它是在WHAM!数据集的sep_clean任务上进行训练的。
data: n_src: 2 mode: min nondefault_nsrc: None sample_rate: 8000 segment: 3 task: sep_clean train_dir: data/wav8k/min/tr/ valid_dir: data/wav8k/min/cv/ filterbank: kernel_size: 16 n_filters: 512 stride: 8 main_args: exp_dir: exp/wham gpus: -1 help: None masknet: bn_chan: 128 hid_chan: 512 mask_act: relu n_blocks: 8 n_repeats: 3 n_src: 2 skip_chan: 128 optim: lr: 0.001 optimizer: adam weight_decay: 0.0 positional arguments: training: batch_size: 24 early_stop: True epochs: 200 half_lr: True num_workers: 4
si_sdr: 16.21326632846293 si_sdr_imp: 16.21441705664987 sdr: 16.615180021738933 sdr_imp: 16.464137807433435 sir: 26.860503975131923 sir_imp: 26.709461760826414 sar: 17.18312813480803 sar_imp: -131.99332048277296 stoi: 0.9619940905157323 stoi_imp: 0.2239480672473015
此作品"ConvTasNet_WHAM!_sepclean"是基于 CSR-I (WSJ0) Complete 由 LDC 创作的,仅用于 LDC User Agreement for Non-Members (仅限研究)。“ConvTasNet_WHAM!_sepclean”由Manuel Pariente根据 Attribution-ShareAlike 3.0 Unported 许可证授权。