Canadian researchers said they have created a technology tool that can more accurately detect depression in the voice. They’d like to see it translated into real-world applications that alert care providers or individuals to emerging mood problems.
The approach uses machine-learning algorithms that recognize the signs of depression in acoustic cues. It builds on past research showing that vocal timbre is a clue to our mood states, reported Eleni Stroulia, Ph.D., and colleague Mashrura Tasnim of the University of Alberta.
Stroulia foresees the tool being employed in an app that collects voice samples from the user. “The app, running on the user’s phone, will recognize and track indicators of mood, such as depression, over time. Much like you have a step counter on your phone, you could have a depression indicator based on your voice,” explained.
Depression in older adults can be difficult to recognize, and eldercare providers may therefore miss signs of trouble, according to the National Institutes on Aging.
Mental Health America estimates that more than two million Americans aged 65 and older suffer from some form of the condition.
