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cs.SD2025

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…

cs.SD2025

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)…

cs.SD2024

The VoiceMOS Challenge 2024: Beyond Speech Quality Prediction

Wen-Chin Huang, Szu-Wei Fu, Erica Cooper +5

We present the third edition of the VoiceMOS Challenge, a scientific initiative designed to advance research into automatic prediction of human speech ratings. There were three tra…

cs.SD2024

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…

cs.SD2024

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…