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arXiv Machine Learning By Anh L Tran, Arjee Javellana Restar, Bereket Kindo

Acoustic Biomarkers for Alzheimer's Disease Detection from Spontaneous Speech

Read the original on arXiv Machine Learning →

The study explores acoustic biomarkers derived from spontaneous speech to differentiate Alzheimer's disease patients from healthy controls. Using a structured picture‑description task, low‑level prosodic, spectral, and temporal features were extracted and fed into various machine learning classifiers. The best models achieved clinically meaningful separation between diagnostic groups, indicating that non‑invasive audio screening could aid early detection of dementia.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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