8 citations · 21 across the 5 of their papers we have counts for
6 papers
ConferencingSpeech 2022 Challenge: Non-intrusive Objective Speech Quality Assessment (NISQA) Challenge for Online Conferencing Applications
Gaoxiong Yi, Wei Xiao, Yiming Xiao +10
With the advances in speech communication systems such as online conferencing applications, we can seamlessly work with people regardless of where they are. However, during online…
Generalized Spatio-Temporal RNN Beamformer for Target Speech Separation
Yong Xu, Zhuohuang Zhang, Meng Yu +2
Although the conventional mask-based minimum variance distortionless response (MVDR) could reduce the non-linear distortion, the residual noise level of the MVDR separated speech i…
Multi-channel Multi-frame ADL-MVDR for Target Speech Separation
Zhuohuang Zhang, Yong Xu, Meng Yu +4
Many purely neural network based speech separation approaches have been proposed to improve objective assessment scores, but they often introduce nonlinear distortions that are har…
ADL-MVDR: All deep learning MVDR beamformer for target speech separation
Zhuohuang Zhang, Yong Xu, Meng Yu +3
Speech separation algorithms are often used to separate the target speech from other interfering sources. However, purely neural network based speech separation systems often cause…
Investigation of Phase Distortion on Perceived Speech Quality for Hearing-impaired Listeners
Zhuohuang Zhang, Donald S. Williamson, Yi Shen
Phase serves as a critical component of speech that influences the quality and intelligibility. Current speech enhancement algorithms are beginning to address phase distortions, bu…
On Loss Functions and Recurrency Training for GAN-based Speech Enhancement Systems
Zhuohuang Zhang, Chengyun Deng, Yi Shen +5
Recent work has shown that it is feasible to use generative adversarial networks (GANs) for speech enhancement, however, these approaches have not been compared to state-of-the-art…