A new approach allows “smart” machines to understand sounds other than speech
Robots can already discern and react to speech thanks to voice-recognition software such as the iPhone’s Siri. But “smart” machines still struggle with most other sounds. “In some sense, it’s almost a simpler problem, but there hasn’t been a lot of work on noise in the environment,” says roboticist Joseph Romano of Rethink Robotics in Boston. “It hasn’t been in the loop for robotic feedback.”
Now Romano is letting robots listen in on more than our conversations. He and his collaborators at the University of Pennsylvania have created a software tool called ROAR (short for robotic operating system open-source audio recognizer) that allows roboticists to train machines to respond to a much wider range of sounds. As described in a recent issue of Autonomous Robots, the tool’s chief requirement is a microphone.
To begin training, the robot’s microphone first captures ambient sounds, which ROAR scrubs of noisy static. Next the operator teaches ROAR to recognize key sounds by repeatedly performing a specific action—such as shutting a door or setting off a smartphone alarm—and tagging the unique audio signature while the robot listens. Finally, the program creates a general model of the sound of each action from that set of training clips.
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