AI speech clock predicts ageing from four minutes of voice recording

October 1, 2026 at 12:35 AM2 min

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Scientists have developed an AI 'speech clock' that estimates a person's ageing rate from four minutes of voice recording. The clock calculates a 'speech age gap' between predicted and chronological age, and large gaps were strongly associated with cognitive impairment. The findings were published today in Science Advances.

Key Facts

The speech clock was trained on recordings from 2,928 Spanish speakers across Argentina, Chile, Colombia, Mexico and Peru.
The model extracts more than 700 vocal features, including pitch and vocabulary range, to predict age.
Large speech age gaps were strongly associated with cognitive issues such as those arising in dementia.
The study was published today in the journal Science Advances.

The Speech Clock

The speech clock draws on hundreds of vocal features, including pitch and talking speed, to estimate a person's age. Researchers calculated a 'speech age gap' for each individual: the difference between the age predicted by the clock and their chronological age. Large speech age gaps were strongly associated with cognitive issues, such as those that arise in dementia. Neuroscientist Agustín Ibáñez at Adolfo Ibáñez University in Santiago, a co-author of the study, said: 'We can see a huge predictive value, just with a very simple four minutes of speech recordings.'

Study Design

Ibáñez and his colleagues recorded 2,928 Spanish speakers from Argentina, Chile, Colombia, Mexico and Peru while they completed various speech tasks. The group included healthy individuals and people with mild cognitive impairment, Alzheimer's disease, or other forms of dementia. Machine-learning algorithms extracted more than 700 speech characteristics that can change with ageing and dementia, such as pitch and vocabulary range. The speech clock could distinguish between healthy individuals and those with some form of cognitive impairment.

Potential Applications

The speech clock could be a boon for tracking ageing in low-resource regions because it does not rely on expensive or invasive technologies such as brain scans and blood tests. Jed Meltzer, a cognitive neuroscientist at the University of Toronto who was not involved in the study, called it 'a very impressive piece of work'. Speaking involves a 'huge amount of brain work', Ibáñez said, making speech a useful window into the ageing process.