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GAANet: Global-guided Asymmetric Attention Network for Audio-Visual Speech Separation
Multi-scale design is crucial for efficient audio-visual speech separation, yet effectively modeling multi-scale information for audio-visual feature fusion remains challenging. We argue that the limited capacity of existing approaches primarily arises from: 1) treating features from different modal
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