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> it's an insanely hard problem Not much: each participant has a pair of (amplitude, phase) values for each microphone. Filtering human voices and correlating
by eeZah7Ux 7y ago
> it's an insanely hard problem
Not much: each participant has a pair of (amplitude, phase) values for each microphone. Filtering human voices and correlating sources to find the phase is not new.
- jcims 7y agoAgree. It's even easy to do manually in audacity with recorded tracks. There are probably some ML innovations here (maybe isolating the voice signal from the background in a way that lets you label the phase info sufficiently to correlate it) but the main innovation that I can see is packaging it in a way that's useful in this context.
- crazygringo 7y agoThat's not how amplitude and phase work, you don't "set them" on a microphone. Filtering sources isn't new, of course, and doing it manually fiddling around with a recording you already made is one thing. But doing it in automatically in real-time on equipment with unknown characteristics that leaves zero ghost signal behind... is, yes, insanely hard.
- eeZah7Ux 7y ago> That's not how amplitude and phase work, you don't "set them" on a microphone. I never said you "set them". The obviously are a product of the location of the microphone in relation to the speaker.