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Alzheimer's disease and related dementia (ADRD) remain largely undiagnosed, as early cognitive symptoms are rarely captured by structured clinical data. Natural speech offers a sensitive, non-invasive window into cognitive decline that structured clinical data cannot provide. This study validates conversational speech from phone calls and participant verbal communication as a biomarker for early cognitive impairment detection. Using an attention-based fusion model across 175 participants, structured clinical data alone achieved AUC = 0.74; adding phone calls improved performance (AUC = 0.76), and participant verbal communication yielded the largest gains (AUC = 0.90). The best configuration achieved AUC = 0.92 and F1 = 83.08, establishing naturalistic speech as a scalable, non-invasive biomarker in clinical settings.