Called EarIO, this ‘earable’, or wearable earphone device, was developed by Cornell researchers and is designed to bounce sound off the cheeks before transforming the echoes into an avatar of a person’s entire moving face. The research team was led by Cheng Zhang and this device transmits facial movements to a smartphone in real-time.
It has compatibility with commercially available headsets for hands-free, cordless video conferencing. Typically face-tracking devices are clunky, heavy and energy-hungry, but acoustic technology takes are of all those issues, while increasing battery life. EarIO essentially works like a ship sending out sonar pulses, as it has a speaker on each side of the earphone that sends these to the sides of the face. A microphone then picks up the echoes and as the wearer makes expressions, a deep learning algorithm uses AI to continually process the data and translate the shifting echoes into facial expressions. Who knows? You may even find this in the Meta Store should EarIO be sold to Mark Zuckerberg.
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Through the power of AI, the algorithm finds complex connections between muscle movement and facial expressions that human eyes cannot identify. We can use that to infer complex information that is harder to capture – the whole front of the face,” said Ke Li, co-author and doctoral student in the field of information science.
