Waves Clarity Vx

Clarity Vx uses a machine learning model trained specifically to separate speech from background noise, aiming at problems like traffic, air conditioning hum, or a noisy remote guest's home office.

It's become a go to for podcast editors handling remote interviews recorded on inconsistent home setups, since it's noticeably more effective on genuinely noisy material than a traditional noise gate or static noise print.

The processing is powerful enough that overusing it introduces its own artifacts, a slightly underwater or hollow quality to the voice, so it needs a light touch and A/B comparison rather than maxing every slider.

For remote heavy shows, it earns its place in the chain quickly, but it's meant for genuinely noisy problem audio, not a default processing step on every track.