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 per cent accuracy, a significant improvement on earlier studies that achieved only about 55 per cent 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.