KAWAKO-in-GAYHUB / DPCRN_DNS3

Implementation of paper "DPCRN: Dual-Path Convolution Recurrent Network for Single Channel Speech Enhancement"

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DPCRN_DNS3

Implementation of paper "DPCRN: Dual-Path Convolution Recurrent Network for Single Channel Speech Enhancement". This work got the third place in Deep Noise Suppression Challenge.

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

Note that the real-time inference can only run on the tensorflow=1.x.

The final results on the blind test set of DNS3 is available on https://github.com/Le-Xiaohuai-speech/DPCRN_DNS3_Results.

run python main.py to test the model on a single file.

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Implementation of paper "DPCRN: Dual-Path Convolution Recurrent Network for Single Channel Speech Enhancement"


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