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eess.AS2026
Towards Lightweight Adaptation of Speech Enhancement Models in Real-World Environments
Longbiao Cheng, Shih-Chii Liu
Recent studies have shown that post-deployment adaptation can improve the robustness of speech enhancement models in unseen noise conditions. However, existing methods often incur…
eess.AS2025
Modulating State Space Model with SlowFast Framework for Compute-Efficient Ultra Low-Latency Speech Enhancement
Longbiao Cheng, Ashutosh Pandey, Buye Xu +3
Deep learning-based speech enhancement (SE) methods often face significant computational challenges when needing to meet low-latency requirements because of the increased number of…
eess.AS2024
Dynamic Gated Recurrent Neural Network for Compute-efficient Speech Enhancement
Longbiao Cheng, Ashutosh Pandey, Buye Xu +2
This paper introduces a new Dynamic Gated Recurrent Neural Network (DG-RNN) for compute-efficient speech enhancement models running on resource-constrained hardware platforms. It l…