English(EN) RAMamba-Net: A Reliability-Aware and Mamba-Based Multimodal Fusion Network for Auditory Attention Detection

新的RAMamba-Net融合EEG和EOG以改进听觉注意力解码

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-12 04:00

研究人员开发了RAMamba-Net，一种用于听觉注意力解码（AAD）的新型多模态融合网络。该网络整合了脑电图（EEG）和眼电图（EOG）信号，以改进对注意力说话者的识别，这是高级助听设备和人机交互的关键功能。RAMamba-Net利用Mamba增强的Transformer处理时间动态和特定频段的EEG模式，而双分支编码器则处理EOG数据。一项关键创新是其可靠性感知模块，该模块动态加权模态贡献，以增强融合和对抗信号变化的鲁棒性。 AI

影响这种多模态融合方法可以提高用于辅助技术和人机交互的AI系统的准确性和鲁棒性。

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arXiv cs.AI TIER_1 English(EN) · Xingyi He, Ziwei Wang, Dongrui Wu · 2026-09-12 04:00

RAMamba-Net：一种可靠性感知、基于Mamba的多模态融合网络，用于听觉注意力检测

arXiv:2609.11372v1 Announce Type: new Abstract: Auditory attention decoding (AAD) identifies the attended speaker from physiological signals, supporting neuro-steered hearing devices and natural human-machine interaction. Electroencephalography (EEG) is the dominant modality for …

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RAMamba-Net：一种可靠性感知、基于Mamba的多模态融合网络，用于听觉注意力检测

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