Washington: Researchers have developed a new computer programme for smartphones that gauges human feelings through speech with a greater accuracy.
The programme developed by engineers at the University of Rochester, surprisingly, doesn't look at the meaning of the words.
"We actually used recordings of actors reading out the date of the month, it really doesn't matter what they say, it's how they're saying it that we're interested in," said researcher Wendi Heinzelman.
The programme analyses 12 features of speech, such as pitch and volume, to identify one of six emotions from a sound recording. And it achieves 81 percent accuracy, a significant improvement on earlier studies that achieved only about 55 percent accuracy.
The research has already been used to develop a prototype of an app. The app displays either a happy or sad face after it records and analyses the user's voice. It was built by one of Heinzelman's graduate students, Na Yang, during a summer internship at Microsoft Research.
"The research is still in its early days," Heinzelman added, "but it is easy to envision a more complex app that could use this technology for everything from adjusting the colours displayed on your mobile to playing music fitting to how you're feeling after recording your voice."
Heinzelman is collaborating with Rochester psychologists Melissa Sturge-Apple and Patrick Davies, who are currently studying the interactions between teenagers and their parents.
"A reliable way of categorising emotions could be very useful in our research," Sturge-Apple said in a statement.
"It would mean that a researcher doesn't have to listen to the conversations and manually input the emotion of different people at different stages."
Teaching a computer to understand emotions begins with recognising how humans do so.
"You might hear someone speak and think 'oh, he sounds angry!' But what is it that makes you think that?" asks Sturge-Apple. She explained that emotion affects the way people speak by altering the volume, pitch and even the harmonics of their speech.
"We don't pay attention to these features individually, we have just come to learn what angry sounds like, particularly for people we know," she added.