56 citations · 110 across the 24 of their papers we have counts for
5 papers · 1 filter
Leveraging Mamba with Full-Face Vision for Audio-Visual Speech Enhancement
Rong Chao, Wenze Ren, You-Jin Li +5
Recent Mamba-based models have shown promise in speech enhancement by efficiently modeling long-range temporal dependencies. However, models like Speech Enhancement Mamba (SEMamba)…
Exploiting Consistency-Preserving Loss and Perceptual Contrast Stretching to Boost SSL-based Speech Enhancement
Muhammad Salman Khan, Moreno La Quatra, Kuo-Hsuan Hung +3
Self-supervised representation learning (SSL) has attained SOTA results on several downstream speech tasks, but SSL-based speech enhancement (SE) solutions still lag behind. To add…
Self-Supervised Speech Quality Estimation and Enhancement Using Only Clean Speech
Szu-Wei Fu, Kuo-Hsuan Hung, Yu Tsao +1
Speech quality estimation has recently undergone a paradigm shift from human-hearing expert designs to machine-learning models. However, current models rely mainly on supervised le…
MetricGAN-U: Unsupervised speech enhancement/ dereverberation based only on noisy/ reverberated speech
Szu-Wei Fu, Cheng Yu, Kuo-Hsuan Hung +2
Most of the deep learning-based speech enhancement models are learned in a supervised manner, which implies that pairs of noisy and clean speech are required during training. Conse…
Speech Recovery for Real-World Self-powered Intermittent Devices
Yu-Chen Lin, Tsun-An Hsieh, Kuo-Hsuan Hung +4
The incompleteness of speech inputs severely degrades the performance of all the related speech signal processing applications. Although many researches have been proposed to addre…