Google acquires SlickLogin: dogs go wild!
SlickLogin, an Israeli start-up, is behind the technology that allows websites to verify a user's identity by using sound waves. It works by playing a uniquely generated, nearly-silent sound through your computer speakers, which is picked up by an app on your smartphone. The app analyses the sound and sends a signal back to confirm your identity.
The firm confirmed the acquisition on its website but did not provide any financial details of the deal.
Too bad they don't still put whistles inside packages of Cap'n Crunch cereal!
(Score: 1) by Angry Jesus on Tuesday February 18 2014, @06:08AM
It takes pretty good test equipment (Rohde & Shwartz) and an anechoic chamber to decently characterize a microphone.
You are thinking about it completely in reverse - this isn't about minimizing distortion, it is simply about distinguishing between different units. Similar to the way that forensic DNA matching only looks at 10-12 markers when that is a tiny fraction necessary to describe a human.
The frequency response of the system is mic(f) * speakers(f). If speakers change, the response changes as well
That's far too simplistic. Off the top of my head I can think of at least one method that isn't affected so straight-forwardly - measuring harmonic response ratios. Even if the speakers' output levels vary at a specific frequency, the microphone will have its own set of harmonics in relation to the generated tones. The speaker will have its own harmonics too, but all that extra noise won't matter because we are only looking for the harmonic signature of the microphone. I'm sure there are other relationships that could be profiled if someone were to spend more than 30 seconds thinking about it.