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Found 5 papers, 1 papers with code
DMCE: Diffusion Model Channel Enhancer for Multi-User Semantic Communication Systems
To address this, this paper proposes a diffusion model (DM)-based channel enhancer (DMCE) for improving the performance of multi-user semantic communication, with the DM learning the particular data distribution of channel effects on the transmitted semantic features.
GLD-Net: Improving Monaural Speech Enhancement by Learning Global and Local Dependency Features with GLD Block
For monaural speech enhancement, contextual information is important for accurate speech estimation.
U-Former: Improving Monaural Speech Enhancement with Multi-head Self and Cross Attention
For supervised speech enhancement, contextual information is important for accurate spectral mapping.
Multi-layer Feature Fusion Convolution Network for Audio-visual Speech Enhancement
Most of recent AV speech enhancement approaches separately process the acoustic and visual features and fuse them via a simple concatenation operation.
AMFFCN: Attentional Multi-layer Feature Fusion Convolution Network for Audio-visual Speech Enhancement
Audio-visual speech enhancement system is regarded to be one of promising solutions for isolating and enhancing speech of desired speaker.
