1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.SD2025
Loud-loss: A Perceptually Motivated Loss Function for Speech Enhancement Based on Equal-Loudness Contours
Zixuan Li, Xueliang Zhang, Changjiang Zhao +5
The mean squared error (MSE) is a ubiquitous loss function for speech enhancement, but its problem is that the error cannot reflect the auditory perception quality. This is because…
eess.AS2024★ 1 cited
SICRN: Advancing Speech Enhancement through State Space Model and Inplace Convolution Techniques
Changjiang Zhao, Shulin He, Xueliang Zhang
Speech enhancement aims to improve speech quality and intelligibility, especially in noisy environments where background noise degrades speech signals. Currently, deep learning met…