5 papers
An Investigation of Incorporating Mamba for Speech Enhancement
Rong Chao, Wen-Huang Cheng, Moreno La Quatra +4
This work aims to investigate the use of a recently proposed, attention-free, scalable state-space model (SSM), Mamba, for the speech enhancement (SE) task. In particular, we emplo…
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)…
Linguistic Knowledge Transfer Learning for Speech Enhancement
Kuo-Hsuan Hung, Xugang Lu, Szu-Wei Fu +4
Linguistic knowledge plays a crucial role in spoken language comprehension. It provides essential semantic and syntactic context for speech perception in noisy environments. Howeve…
Deep Learning-based Non-Intrusive Multi-Objective Speech Assessment Model with Cross-Domain Features
Ryandhimas E. Zezario, Szu-Wei Fu, Fei Chen +3
In this study, we propose a cross-domain multi-objective speech assessment model called MOSA-Net, which can estimate multiple speech assessment metrics simultaneously. Experimental…
RankUp: Boosting Semi-Supervised Regression with an Auxiliary Ranking Classifier
Pin-Yen Huang, Szu-Wei Fu, Yu Tsao
State-of-the-art (SOTA) semi-supervised learning techniques, such as FixMatch and it's variants, have demonstrated impressive performance in classification tasks. However, these me…