514 citations · 674 across the 27 of their papers we have counts for
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eess.AS2022
Boosting Self-Supervised Embeddings for Speech Enhancement
Kuo-Hsuan Hung, Szu-wei Fu, Huan-Hsin Tseng +3
Self-supervised learning (SSL) representation for speech has achieved state-of-the-art (SOTA) performance on several downstream tasks. However, there remains room for improvement i…
eess.AS2022★ 2 cited
MTI-Net: A Multi-Target Speech Intelligibility Prediction Model
Ryandhimas E. Zezario, Szu-wei Fu, Fei Chen +3
Recently, deep learning (DL)-based non-intrusive speech assessment models have attracted great attention. Many studies report that these DL-based models yield satisfactory assessme…