/SKIP-DPCRN

Primary LanguagePython

SKIP-DPCRN

Implementation of the DPCRN model with skipping strategy in the submitted manuscript for IEEE/ACM TASLP.

Requirements

tensorflow>=1.14, numpy, matplotlib, librosa, sondfile.

Run

python main.py --mode train --cuda 0 --experimentName experiment_1
python main.py --mode test --cuda 0 --ckpt PATH_OF_PRETRAINED_MODEL --test_dir PATH_OF_NOISY_AUDIO --output_dir PATH_OF_ENHANCED_AUDIO

Reference

  1. X. Le, H. Chen, K. Chen, and J. Lu, “DPCRN: Dual-Path Convolution Recurrent Network for Single Channel Speech Enhancement,” Proc. Interspeech 2021, pp. 2811–2815, 2021. (https://github.com/Le-Xiaohuai-speech/DPCRN_DNS3)