A new study conducted by computing scientists at the University of Alberta has found that advanced AI algorithm can more effectively detect depression through a person's voice. Scientists conducted this research based on several past studies that suggested that the timbre of a person's voice contains information about his or her mood.
During the research, PhD student Mashrura Tasnim and Professor Eleni Stroulia used standard benchmark datasets and developed a methodology that combined several machine-learning algorithms to accurately detect depression among people using acoustic signs.
Eleni Stroulia, after the research, revealed that their research was aimed to develop meaningful technology that will help people suffering from psychological disorders like depression.
"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," said Stroulia in a recent statement.
The research report titled 'Detecting Depression from Voice', recently presented at the Canadian Conference on Artificial Intelligence added that such tools powered by artificial intelligence will help people to understand their own mood changes over time.
"This work, developing more accurate detection in standard benchmark data sets, is the first step," added Stroulia.
A few weeks back, another study conducted by experts at the University of North Carolina school of research had found that brain stimulation is capable of significantly reducing the symptoms of depression. The research report revealed that sending an electrical current through electrodes attached to the scalp improved depression symptoms of 70 percent participants who took part in the clinical study.
Another study had previously suggested that microdoses of magic mushroom are quite helpful in treating depression.