AI Analysis of Speech Patterns Could Predict Early Dementia Risk
Researchers from Baycrest, the University of Toronto, and York University have discovered that subtle characteristics in everyday speech, such as pauses and filler words, are closely linked to executive function, which includes memory, planning, and attention. The study utilized artificial intelligence to analyze speech recordings, identifying hundreds of subtle features that could predict cognitive performance. This research suggests that natural speech patterns could serve as indicators of brain health, potentially offering a simpler and more frequent method of detecting early signs of dementia compared to traditional cognitive tests. 
