3 citations · 3 across the 1 of their papers we have counts for
4 papers
Exploring Resolution-Wise Shared Attention in Hybrid Mamba-U-Nets for Improved Cross-Corpus Speech Enhancement
Nikolai Lund Kühne, Jesper Jensen, Jan Ãstergaard +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…
MambAttention: Mamba with Multi-Head Attention for Generalizable Single-Channel Speech Enhancement
Nikolai Lund Kühne, Jesper Jensen, Jan Ãstergaard +1
With new sequence models like Mamba and xLSTM, several studies have shown that these models match or outperform the state-of-the-art in single-channel speech enhancement and audio…
xLSTM-SENet: xLSTM for Single-Channel Speech Enhancement
Nikolai Lund Kühne, Jan Ãstergaard, 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…
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…