2 citations · 7 across the 15 of their papers we have counts for
5 papers · 1 filter
Hierarchical Modeling of Spatial Cues via Spherical Harmonics for Multi-Channel Speech Enhancement
Jiahui Pan, Shulin He, Hui Zhang +1
Multi-channel speech enhancement utilizes spatial information from multiple microphones to extract the target speech. However, most existing methods do not explicitly model spatial…
PDPCRN: Parallel Dual-Path CRN with Bi-directional Inter-Branch Interactions for Multi-Channel Speech Enhancement
Jiahui Pan, Shulin He, Tianci Wu +2
Multi-channel speech enhancement seeks to utilize spatial information to distinguish target speech from interfering signals. While deep learning approaches like the dual-path convo…
MC-SpEx: Towards Effective Speaker Extraction with Multi-Scale Interfusion and Conditional Speaker Modulation
Jun Chen, Wei Rao, Zilin Wang +5
The previous SpEx+ has yielded outstanding performance in speaker extraction and attracted much attention. However, it still encounters inadequate utilization of multi-scale inform…
Gesper: A Restoration-Enhancement Framework for General Speech Reconstruction
Wenzhe Liu, Yupeng Shi, Jun Chen +5
This paper describes a real-time General Speech Reconstruction (Gesper) system submitted to the ICASSP 2023 Speech Signal Improvement (SSI) Challenge. This novel proposed system is…
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…