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New sensor to help smartphones hear through cocktail party
New sensor to help smartphones hear through cocktail party. People trying to talk to Apple\'s electronic personal assistant Siri in a crowded place may soon no longer have to look like they are about to eat their iPhones, thanks to a new invention by Duke University engineers.
People trying to talk to Apple's electronic personal assistant Siri in a crowded place may soon no longer have to look like they are about to eat their iPhones, thanks to a new invention by Duke University engineers.
"We've invented a sensing system that can efficiently solve an interesting problem that modern technology has to deal with on a daily basis," said the paper's lead author Abel Xie. "This could improve the performance of voice-activated devices like smartphones and game consoles," Xie added.
The sensor developed by Duke engineers can determine the direction of a sound and extract it from the surrounding background noise. Once miniaturised, the device could have applications in voice-command electronics, medical sensing devices that use waves, like ultrasound, and hearing aids and cochlear implants.
The proof-of-concept device looks a bit like a thick, plastic, pie-shaped honeycomb split into dozens of slices. While the honeycomb openings may all look the same, their depth varies from hole to hole.
"The cavities behave like soda bottles when you blow across their tops. The depth of the cavities affects the pitch of the sound they make, and this changes the incoming sound in a subtle but detectable way," said Steve Cummer, professor of electrical and computer engineering at Duke.
When a sound wave gets to the device, it gets slightly distorted by the cavities. And that distortion has a specific signature depending what slice of the pie it passed over. After being picked up by a microphone on the other side, the sound is transmitted to a computer that is able to separate the jumble of noises based on these unique distortions.
The researchers tested their invention in multiple trials by simultaneously sending three identical sounds at the sensor from three different directions. It was able to distinguish between them with a 96.7 percent accuracy rate. The findings were described in the Proceedings of the National Academy of Sciences.
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