By studying videos from high-stakes court cases, researchers at University of Michigan (UM) are building the lie-detecting software based on real-world data. It was up to 75 per cent accurate in identifying who was being deceptive (as defined by trial outcomes), compared with humans' scores of just above 50 per cent, researchers said.

The researchers found that lying individuals moved their hands more. They tried to sound more certain. They also looked their questioners in the eye a bit more often than those presumed to be telling the truth, among other behaviors.

In laboratory experiments, it's difficult to create a setting that motivates people to truly lie, said Rada Mihalcea, professor at UM, who leads the project with Mihai Burzo, assistant professor at UM-Flint. We can offer a reward if people can lie well - pay them to convince another person that something false is true.

The videos include testimony from both defendants and witnesses. In half of the clips, the subject is deemed to be lying. They then analysis  how often subjects used various words or categories of words. They also counted the gestures in the videos using a standard coding scheme for interpersonal interactions that scores nine different motions of the head, eyes, brow, mouth and hands.

The researchers fed the data into their system and let it sort the videos. When it used input from both the speaker's words and gestures, it was 75 per cent accurate in identifying who was lying. In the clips of people lying, the researchers found some common behaviors, such as scowling or grimacing of the whole face.

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