Search Results for author: Shubo Lv

Found 8 papers, 2 papers with code

DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement

7 code implementations Interspeech 2020 Yanxin Hu, Yun Liu, Shubo Lv, Mengtao Xing, Shimin Zhang, Yihui Fu, Jian Wu, Bihong Zhang, Lei Xie

Speech enhancement has benefited from the success of deep learning in terms of intelligibility and perceptual quality.

Speech Enhancement Audio and Speech Processing Sound

DCCRN+: Channel-wise Subband DCCRN with SNR Estimation for Speech Enhancement

no code implementations16 Jun 2021 Shubo Lv, Yanxin Hu, Shimin Zhang, Lei Xie

Deep complex convolution recurrent network (DCCRN), which extends CRN with complex structure, has achieved superior performance in MOS evaluation in Interspeech 2020 deep noise suppression challenge (DNS2020).

Speech Enhancement

S-DCCRN: Super Wide Band DCCRN with learnable complex feature for speech enhancement

no code implementations16 Nov 2021 Shubo Lv, Yihui Fu, Mengtao Xing, Jiayao Sun, Lei Xie, Jun Huang, Yannan Wang, Tao Yu

In speech enhancement, complex neural network has shown promising performance due to their effectiveness in processing complex-valued spectrum.

Denoising Speech Denoising +1

spatial-dccrn: dccrn equipped with frame-level angle feature and hybrid filtering for multi-channel speech enhancement

no code implementations17 Oct 2022 Shubo Lv, Yihui Fu, Yukai Jv, Lei Xie, Weixin Zhu, Wei Rao, Yannan Wang

Recently, multi-channel speech enhancement has drawn much interest due to the use of spatial information to distinguish target speech from interfering signal.

Denoising Speech Enhancement

DCCRN-KWS: an audio bias based model for noise robust small-footprint keyword spotting

no code implementations21 May 2023 Shubo Lv, Xiong Wang, Sining Sun, Long Ma, Lei Xie

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.

Denoising Multi-Task Learning +4

MBTFNet: Multi-Band Temporal-Frequency Neural Network For Singing Voice Enhancement

no code implementations6 Oct 2023 Weiming Xu, Zhouxuan Chen, Zhili Tan, Shubo Lv, Runduo Han, Wenjiang Zhou, Weifeng Zhao, Lei Xie

A typical neural speech enhancement (SE) approach mainly handles speech and noise mixtures, which is not optimal for singing voice enhancement scenarios.

Music Source Separation Speech Enhancement

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