Gated Multi-Graph Fusion via Graph Attention Networks for Alzheimer's Disease Detection

arXiv:2606.31186v1 Announce Type: new Abstract: Spontaneous speech is a vital non-invasive biomarker for Alzheimer's Disease (AD), yet many systems overlook non-linear structural disruptions and clinical heterogeneity in pathological language. We propose a Multi-View Gated Graph Attention Network that transcribes audio via Automatic Speech Recognition (ASR) to construct semantic, dependency, and co-occurrence graphs, characterizing speech through a "content-structure-flow" framework. Notably, the co-occurrence graph leverages Pointwise Mutual Information (PMI) from a normative corpus to quanti

Source: arXiv cs.CL — read the full report at the original publisher.

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