activity
20212023
most citedEnd-to-End Complex-Valued Multidilated Convolutional Neural Network for Joint Acoustic Echo Cancellation and Noise Suppression

13 citations · 16 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SD2023★ 1 cited

MossFormer2: Combining Transformer and RNN-Free Recurrent Network for Enhanced Time-Domain Monaural Speech Separation

Shengkui Zhao, Yukun Ma, Chongjia Ni +7

Our previously proposed MossFormer has achieved promising performance in monaural speech separation. However, it predominantly adopts a self-attention-based MossFormer module, whic…

cs.SD2023

ACA-Net: Towards Lightweight Speaker Verification using Asymmetric Cross Attention

Jia Qi Yip, Tuan Truong, Dianwen Ng +7

In this paper, we propose ACA-Net, a lightweight, global context-aware speaker embedding extractor for Speaker Verification (SV) that improves upon existing work by using Asymmetri…

cs.SD2023

D2Former: A Fully Complex Dual-Path Dual-Decoder Conformer Network using Joint Complex Masking and Complex Spectral Mapping for Monaural Speech Enhancement

Shengkui Zhao, Bin Ma

Monaural speech enhancement has been widely studied using real networks in the time-frequency (TF) domain. However, the input and the target are naturally complex-valued in the TF…

cs.SD2023★ 1 cited

MossFormer: Pushing the Performance Limit of Monaural Speech Separation using Gated Single-Head Transformer with Convolution-Augmented Joint Self-Attentions

Shengkui Zhao, Bin Ma

Transformer based models have provided significant performance improvements in monaural speech separation. However, there is still a performance gap compared to a recent proposed u…

cs.SD2022★ 1 cited

FRCRN: Boosting Feature Representation using Frequency Recurrence for Monaural Speech Enhancement

Shengkui Zhao, Bin Ma, Karn N. Watcharasupat +1

Convolutional recurrent networks (CRN) integrating a convolutional encoder-decoder (CED) structure and a recurrent structure have achieved promising performance for monaural speech…

eess.AS2021★ 13 cited

End-to-End Complex-Valued Multidilated Convolutional Neural Network for Joint Acoustic Echo Cancellation and Noise Suppression

Karn N. Watcharasupat, Thi Ngoc Tho Nguyen, Woon-Seng Gan +2

Echo and noise suppression is an integral part of a full-duplex communication system. Many recent acoustic echo cancellation (AEC) systems rely on a separate adaptive filtering mod…