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ESPnet2 ENH model
espnet/Wangyou_Zhang_chime4_enh_train_enh_beamformer_mvdr_raw
This model was trained by Wangyou Zhang using chime4 recipe in espnet.
Demo: How to use in ESPnet2
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_beamformer_mvdr_raw
ENH config
expand
config: conf/tuning/train_enh_beamformer_mvdr.yaml
print_config: false
log_level: INFO
dry_run: false
iterator_type: sequence
output_dir: exp/enh_train_enh_beamformer_mvdr_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: 35841
dist_launcher: null
multiprocessing_distributed: true
cudnn_enabled: true
cudnn_benchmark: false
cudnn_deterministic: true
collect_stats: false
write_collected_feats: false
max_epoch: 70
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
- exp/enh_stats_16k/train/noise_ref1_shape
valid_shape_file:
- exp/enh_stats_16k/valid/speech_mix_shape
- exp/enh_stats_16k/valid/speech_ref1_shape
- exp/enh_stats_16k/valid/noise_ref1_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: 500
chunk_shift_ratio: 0.5
num_cache_chunks: 1024
train_data_path_and_name_and_type:
- - dump/raw/tr05_simu_isolated_6ch_track/wav.scp
- speech_mix
- sound
- - dump/raw/tr05_simu_isolated_6ch_track/spk1.scp
- speech_ref1
- sound
- - dump/raw/tr05_simu_isolated_6ch_track/noise1.scp
- noise_ref1
- sound
valid_data_path_and_name_and_type:
- - dump/raw/dt05_simu_isolated_6ch_track/wav.scp
- speech_mix
- sound
- - dump/raw/dt05_simu_isolated_6ch_track/spk1.scp
- speech_ref1
- sound
- - dump/raw/dt05_simu_isolated_6ch_track/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
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: mask_mse
mask_type: PSM^2
use_preprocessor: false
encoder: stft
encoder_conf:
n_fft: 512
hop_length: 128
separator: wpe_beamformer
separator_conf:
num_spk: 1
loss_type: mask_mse
use_wpe: false
wnet_type: blstmp
wlayers: 3
wunits: 300
wprojs: 320
wdropout_rate: 0.0
taps: 5
delay: 3
use_dnn_mask_for_wpe: true
use_beamformer: true
bnet_type: blstmp
blayers: 3
bunits: 512
bprojs: 512
badim: 320
ref_channel: 3
use_noise_mask: true
beamformer_type: mvdr_souden
bdropout_rate: 0.0
decoder: stft
decoder_conf:
n_fft: 512
hop_length: 128
required:
- output_dir
version: 0.9.7
distributed: true
Citing ESPnet
@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},
}
or 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}
}
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