11 citations · 31 across the 8 of their papers we have counts for
8 papers
WTFormer: A Wavelet Conformer Network for MIMO Speech Enhancement with Spatial Cues Peservation
Lu Han, Junqi Zhao, Renhua Peng
Current multi-channel speech enhancement systems mainly adopt single-output architecture, which face significant challenges in preserving spatio-temporal signal integrity during mu…
Reliable and superior elliptic Fourier descriptor normalization and its application software ElliShape with efficient image processing
Hui Wu, Jia-Jie Yang, Chao-Qun Li +3
Elliptic Fourier analysis (EFA) is a powerful tool for shape analysis, which is often employed in geometric morphometrics. However, the normalization of elliptic Fourier descriptor…
A deep complex multi-frame filtering network for stereophonic acoustic echo cancellation
Linjuan Cheng, Chengshi Zheng, Andong Li +3
In hands-free communication system, the coupling between loudspeaker and microphone generates echo signal, which can severely influence the quality of communication. Meanwhile, var…
Two Heads Are Better Than One: A Two-Stage Approach for Monaural Noise Reduction in the Complex Domain
Andong Li, Chengshi Zheng, Renhua Peng +1
In low signal-to-noise ratio conditions, it is difficult to effectively recover the magnitude and phase information simultaneously. To address this problem, this paper proposes a t…
Dynamic Attention Based Generative Adversarial Network with Phase Post-Processing for Speech Enhancement
Andong Li, Chengshi Zheng, Renhua Peng +2
The generative adversarial networks (GANs) have facilitated the development of speech enhancement recently. Nevertheless, the performance advantage is still limited when compared w…
The IOA System for Deep Noise Suppression Challenge using a Framework Combining Dynamic Attention and Recursive Learning
Andong Li, Chengshi Zheng, Renhua Peng +2
This technical report describes our system that is submitted to the Deep Noise Suppression Challenge and presents the results for the non-real-time track. To refine the estimation…
A Recursive Network with Dynamic Attention for Monaural Speech Enhancement
Andong Li, Chengshi Zheng, Cunhang Fan +2
A person tends to generate dynamic attention towards speech under complicated environments. Based on this phenomenon, we propose a framework combining dynamic attention and recursi…
A Time-domain Monaural Speech Enhancement with Feedback Learning
Andong Li, Chengshi Zheng, Linjuan Cheng +2
In this paper, we propose a type of neural network with feedback learning in the time domain called FTNet for monaural speech enhancement, where the proposed network consists of th…