NEW YORK: What if a smartphone app can gauge mood swings via voice analysis and alert you to handle the person accordingly?
Researchers at University of Michigan have developed an app that monitors subtle qualities of a person's voice during everyday phone conversations.
It shows promise for detecting early signs of mood changes in people with bipolar disorder.
"The results give us preliminary proof that we can detect mood states in regular phone calls by analysing broad features and properties of speech, without violating the privacy of those conversations," explained Zahi Karam, a postdoctoral fellow and specialist in machine learning and speech analysis.
The researchers call the project PRIORI, because they hope it will yield a biological marker to prioritise bipolar disorder care to those who need it most urgently to stabilise their moods.
The app runs in the background on an Android smartphone and automatically monitors the patients' voice patterns during any calls made.
The computer programme analyses many characteristics of the sounds — and silences — of each conversation.
"As we collect more data the model will become better, and our ultimate goal is to be able to anticipate swings, so that it may be possible to intervene early," Karam added.
The researchers presented the findings at the International Conference on Acoustics, Speech and Signal Processing in Italy this week.