AI algorithms can now more accurately detect depressed mood using the sound of your voice, according to new research by University of Alberta computing scientists.
AI algorithms can now more accurately detect depressed mood using the sound of your voice, according to new research by University of Alberta computing scientists.
The research was conducted by PhD student Mashrura Tasnim and Professor Eleni Stroulia in the Department of Computing Science. The study builds on past research that suggests that the timbre of our voice contains information about our mood. Using standard benchmark data sets, Tasnim and Stroulia developed a methodology that combines several machine-learning algorithms to recognize depression more accurately using acoustic cues.
The ultimate goal, Stroulia explained, is to develop meaningful applications from this technology.
“A realistic scenario is to have people use an app that will collect voice samples as they speak naturally. 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 as you use the phone.”
Read more at University of Alberta
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