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eess.AS2023
A Deep Representation Learning-based Speech Enhancement Method Using Complex Convolution Recurrent Variational Autoencoder
Yang Xiang, Jingguang Tian, Xinhui Hu +2
Generally, the performance of deep neural networks (DNNs) heavily depends on the quality of data representation learning. Our preliminary work has emphasized the significance of de…
eess.AS2023
LE-SSL-MOS: Self-Supervised Learning MOS Prediction with Listener Enhancement
Zili Qi, Xinhui Hu, Wangjin Zhou +4
Recently, researchers have shown an increasing interest in automatically predicting the subjective evaluation for speech synthesis systems. This prediction is a challenging task, e…