3 papers
cs.SD2025
Exploring Resolution-Wise Shared Attention in Hybrid Mamba-U-Nets for Improved Cross-Corpus Speech Enhancement
Nikolai Lund Kühne, Jesper Jensen, Jan Østergaard +1
Recent advances in speech enhancement have shown that models combining Mamba and attention mechanisms yield superior cross-corpus generalization performance. At the same time, inte…
cs.SD2025
xLSTM-SENet: xLSTM for Single-Channel Speech Enhancement
Nikolai Lund Kühne, Jan Østergaard, Jesper Jensen +1
While attention-based architectures, such as Conformers, excel in speech enhancement, they face challenges such as scalability with respect to input sequence length. In contrast, t…
eess.AS2024
Detecting and Defending Against Adversarial Attacks on Automatic Speech Recognition via Diffusion Models
Nikolai L. Kühne, Astrid H. F. Kitchen, Marie S. Jensen +4
Automatic speech recognition (ASR) systems are known to be vulnerable to adversarial attacks. This paper addresses detection and defence against targeted white-box attacks on speec…