62 citations · 143 across the 11 of their papers we have counts for
4 papers · 1 filter
TEA-PSE 3.0: Tencent-Ethereal-Audio-Lab Personalized Speech Enhancement System For ICASSP 2023 DNS Challenge
Yukai Ju, Jun Chen, Shimin Zhang +6
This paper introduces the Unbeatable Team's submission to the ICASSP 2023 Deep Noise Suppression (DNS) Challenge. We expand our previous work, TEA-PSE, to its upgraded version -- T…
Two-step Band-split Neural Network Approach for Full-band Residual Echo Suppression
Zihan Zhang, Shimin Zhang, Mingshuai Liu +4
This paper describes a Two-step Band-split Neural Network (TBNN) approach for full-band acoustic echo cancellation. Specifically, after linear filtering, we split the full-band sig…
DCCRN+: Channel-wise Subband DCCRN with SNR Estimation for Speech Enhancement
Shubo Lv, Yanxin Hu, Shimin Zhang +1
Deep complex convolution recurrent network (DCCRN), which extends CRN with complex structure, has achieved superior performance in MOS evaluation in Interspeech 2020 deep noise sup…
DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement
Yanxin Hu, Yun Liu, Shubo Lv +6
Speech enhancement has benefited from the success of deep learning in terms of intelligibility and perceptual quality. Conventional time-frequency (TF) domain methods focus on pred…