I’ve seen a lot of hype around Krisp’s “AI-powered virtual microphone,” and frankly, the term gets thrown around with the same precision as “cloud-native” or “synergy.” So let’s deconstruct it.
In a physical sense, your computer has real audio inputs—a built-in mic or a port for your headset. That’s the hardware microphone. When you select “Krisp Microphone” in Zoom or Teams, you’re not selecting a physical device. You’re selecting a software layer that sits between your real mic and the application.
Think of it as a real-time processing filter. Your actual microphone feed goes into Krisp first. The software applies its noise suppression algorithms, stripping out what it deems background noise (keyboard clacks, dog barks, HVAC). What gets passed along to Zoom is this cleaned-up audio stream, now masquerading as a new, “virtual” microphone source.
The real question for the data-skeptic is: what’s the latency and quality cost of this virtual layer? Every benchmark I see is from the vendor. I want to see a reproducible test: same sentence, same room tone, with and without Krisp, measuring waveform differences and processing delay. Anyone run a controlled experiment like that, or are we all just trusting the marketing?
Data skeptic, not a data cynic.