Watch what you say

Your “um” and pauses could reveal early dementia risk

Baycrest Corporate Centre for Geriatric Care

The little pauses, “ums,” and moments when you struggle to find the right word may reveal far more about your brain than anyone realized. Researchers discovered that everyday speech patterns are closely tied to executive function — the mental system that powers memory, planning, focus, and flexible thinking. 

By using AI to analyze natural conversations, the team found they could predict cognitive performance with surprising accuracy, potentially opening the door to simple speech-based tools that could detect early signs of dementia long before traditional testing does.

The way people speak during ordinary conversations could offer valuable insight into brain health, according to new research from Baycrest, the University of Toronto, and York University. Scientists found that subtle speech characteristics, including pauses, filler words such as ('uh,' 'um'), and difficulty retrieving words, are closely connected to executive function, the group of mental abilities involved in memory, planning, attention, and flexible thinking.

The findings provide some of the strongest evidence so far linking natural speech patterns with key cognitive abilities. The work also expands on earlier research showing that older adults who speak more quickly tend to maintain stronger thinking skills over time (Wei et al., 2024).

"The message is clear: speech timing is more than just a matter of style, it's a sensitive indicator of brain health," says Dr. Jed Meltzer, Senior Scientist at Baycrest's Rotman Research Institute and senior author on this study, titled "Natural Speech Analysis Can Reveal Individual Differences in Executive Function Across the Adult Lifespan."

AI Analysis Reveals Hidden Cognitive Clues

For the study, participants were shown detailed images and asked to describe them in their own words. They also completed established tests designed to measure executive function.

Researchers then used artificial intelligence to examine the speech recordings in depth. The AI system detected hundreds of subtle speech features, including the length and frequency of pauses, the use of filler words, and timing-related patterns in speech. These markers consistently predicted how well participants performed on cognitive tests, even after researchers adjusted for factors such as age, sex, and education.

Speech Patterns and Dementia Risk

Executive function naturally weakens with age and is often affected during the early stages of dementia. However, standard cognitive testing can be difficult to repeat frequently because it takes time and people often improve simply from becoming familiar with the tests.

Natural speech may offer a simpler alternative. Because speaking is part of daily life, it can be measured repeatedly and unobtrusively on a large scale. Researchers also noted that speech provides valuable insight into processing speed and overall cognitive function in real-world situations, without requiring strict time limits that are common in many traditional cognitive assessments.

The team believes speech analysis could eventually become a practical way to identify people whose cognitive decline is progressing faster than expected and who may face a higher risk of developing dementia.

"This research sets the stage for exciting opportunities to develop tools that could help track cognitive changes in clinics or even at home. Early detection is critical for any cure or intervention, as dementia involves progressive degeneration of the brain that may be slowed," says Dr. Meltzer.

Future Research on Brain Health Monitoring

The researchers say more long-term studies are needed to follow changes in speech over time and distinguish normal aging from the earliest signs of disease. They also suggest that combining speech analysis with other health measures could make early detection of cognitive decline more accurate, practical, and widely available.

This research was supported by the Mitacs Accelerate program and the Natural Sciences and Engineering Research Council of Canada (NSERC).

Journal Reference:

1. Hsi T. Wei, Dana Kulzhabayeva, Lella Erceg, Mira Kates Rose, Kiah A. Spencer, Jessica Robin, Ellen Bialystok, Jed A. Meltzer. Natural Speech Analysis Can Reveal Individual Differences in Executive Function Across the Adult Lifespan. Journal of Speech, Language, and Hearing Research, 2025; 68 (12): 5708 DOI: 10.1044/2025_JSLHR-24-00268