AI-powered speech clock analyzes biological aging
Scientists have developed a new artificial intelligence model that predicts the rate of biological aging and cognitive health by examining vocal characteristics.
Researchers have designed an artificial intelligence model that determines the rate of biological aging by analyzing more than 700 variables in a person's voice, such as pitch, pace, and vocabulary. Called the 'speech clock', this system enables the early detection of cognitive disorders such as dementia through the speech age gap.
How does the speech clock work?
The system predicts a person's biological age by analyzing a short four-minute voice recording. Evaluating more than 700 parameters such as speech rate, pitch, and vocabulary, machine learning algorithms calculate the difference between chronological age and predicted age.
Its connection to cognitive health
Researchers found that the difference between the predicted age and chronological age is directly related to cognitive impairments such as dementia. It was observed that individuals experiencing cognitive problems had speech ages that appeared more advanced than their actual chronological ages.
Comprehensive data analysis
During the development of the model, voice recordings of a total of 2,928 people from Argentina, Chile, Colombia, Mexico, and Peru were examined. The results obtained were verified by comparing them with traditional biological aging indicators such as p-tau217 protein levels and brain imaging data.
An accessible health tool
The method is expected to offer a lower-cost and more accessible alternative compared to expensive and invasive medical tests. Experts emphasize that more studies are needed for the clinical validation of the system.