Hello,

We noticed you're browsing in private or incognito mode.

To continue reading this article, please exit incognito mode or log in.

Not an Insider? Subscribe now for unlimited access to online articles.

Delight or Frustration? Tough Call.

Media Lab research could help computers—and people—interpret facial expressions

  • by David L. Chandler
  • August 21, 2012
  • Who’s not happy?: A subject exhibits happiness (left) and frustration (right).

Your computer doesn’t know if you’re happy or frustrated. But before long, it may do a better job of telling the difference than your friends do.

Though most people don’t realize it, a recent MIT study found that people who are frustrated often assume an expression that looks like a smile. Computers programmed with information from this research do better at differentiating smiles of delight and frustration than human observers do. The findings could pave the way for computers that assess the emotional states of their users. They could also lead to teaching tools for people who have difficulty interpreting expressions, such as those with autism.

“The goal is to help people with face-to-face communication,” says Ehsan Hoque, a graduate student in the Media Lab’s Affective Computing Group, who worked with Professor Rosalind Picard, SM ’86, ScD ’91, and graduate student Daniel McDuff on the study.

This story is part of the September/October 2012 Issue of the MIT News magazine
See the rest of the issue
Subscribe

Subjects were asked to feign both delight and frustration. They were also asked to fill out a form designed to cause genuine frustration and to watch a video of a cute baby, designed to evoke delight. A webcam recorded their expressions.

When pretending to be frustrated, Hoque says, 90 percent of subjects did not smile. But when genuinely frustrated—after filling out a long online form, only to have everything disappear after they pressed “Submit”—90 percent did make a face that resembled a smile. Still photos showed little difference between the expressions, but video analysis revealed a crucial distinction: typically, happy smiles built up gradually, while frustrated smiles appeared quickly but faded fast. Though people may not know exactly what cues they are responding to, timing has a lot to do with how they interpret expressions. “Getting the timing right is very crucial if you want to be perceived as sincere and genuine with your smiles,” Hoque says.

When the MIT researchers asked a different group of people to interpret still images of these real responses, they got it right only half the time. Understanding the subtleties that reveal underlying emotions is a major goal of this research, Hoque says. “People with autism are taught that a smile means someone is happy,” he says. The research, however, shows it’s not that simple.

The analysis could be useful in creating computers that respond appropriately to the moods of their users. One goal of the Affective Computing Group’s research is to “make a computer that’s more intelligent and respectful,” Hoque says—and one that knows when you’re having a bad day. 

Be the leader your company needs. Implement ethical AI.
Join us at EmTech Digital 2019.

Register now
Next in MIT News
Want more award-winning journalism? Subscribe to Insider Plus.
  • Insider Plus {! insider.prices.plus !}*

    {! insider.display.menuOptionsLabel !}

    Everything included in Insider Basic, plus the digital magazine, extensive archive, ad-free web experience, and discounts to partner offerings and MIT Technology Review events.

    See details+

    Print + Digital Magazine (6 bi-monthly issues)

    Unlimited online access including all articles, multimedia, and more

    The Download newsletter with top tech stories delivered daily to your inbox

    Technology Review PDF magazine archive, including articles, images, and covers dating back to 1899

    10% Discount to MIT Technology Review events and MIT Press

    Ad-free website experience

/3
You've read of three free articles this month. for unlimited online access. You've read of three free articles this month. for unlimited online access. This is your last free article this month. for unlimited online access. You've read all your free articles this month. for unlimited online access. You've read of three free articles this month. for more, or for unlimited online access. for two more free articles, or for unlimited online access.