Analysis of pauses and filler words like "um" identifies early signs of cognitive decline. Researchers linked these specific audio markers to failures in executive function. This discovery enables non-invasive screening using machine learning to detect dementia before clinical symptoms appear. Practitioners can now use speech-based biomarkers for faster, scalable patient diagnostics.