Mild Cognitive Impairment Detection System Based on Unstructured Spontaneous Speech: Longitudinal Dual-Modal Framework

This study presents a noninvasive and scalable approach for early MCI detection by leveraging AM speech data across multiple time points. Through dual-modal analysis and the introduction of an aging trajectory module, our system effectively captures cognitive decline trends over time. Experimental results demonstrate the method's robustness and generalizability, highlighting its potential for real-world, long-term cognitive monitoring.