62 citations · 78 across the 6 of their papers we have counts for
5 papers · 1 filter
DCCRN-KWS: an audio bias based model for noise robust small-footprint keyword spotting
Shubo Lv, Xiong Wang, Sining Sun +2
Real-world complex acoustic environments especially the ones with a low signal-to-noise ratio (SNR) will bring tremendous challenges to a keyword spotting (KWS) system. Inspired by…
Two-stage Neural Network for ICASSP 2023 Speech Signal Improvement Challenge
Mingshuai Liu, Shubo Lv, Zihan Zhang +6
In ICASSP 2023 speech signal improvement challenge, we developed a dual-stage neural model which improves speech signal quality induced by different distortions in a stage-wise div…
spatial-dccrn: dccrn equipped with frame-level angle feature and hybrid filtering for multi-channel speech enhancement
Shubo Lv, Yihui Fu, Yukai Jv +4
Recently, multi-channel speech enhancement has drawn much interest due to the use of spatial information to distinguish target speech from interfering signal. To make full use of s…
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…