activity
20202023
most citedDCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement

62 citations · 78 across the 4 of their papers we have counts for

collaborators

5 papers

eess.AS2023

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…

eess.AS20229 cited

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…

eess.AS20217 cited

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…

cs.SD2021

AISHELL-4: An Open Source Dataset for Speech Enhancement, Separation, Recognition and Speaker Diarization in Conference Scenario

Yihui Fu, Luyao Cheng, Shubo Lv +10

In this paper, we present AISHELL-4, a sizable real-recorded Mandarin speech dataset collected by 8-channel circular microphone array for speech processing in conference scenario.…

eess.AS202062 cited

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…