Krisp

There's a particular type of calling horror that most remote workers know all too well: you're in a meeting with clients, and the delivery driver shows up at your door just as the doorbell rings, and your dog decides that now is the perfect time for Fido's vocal repertoire. Everyone in the meeting can hear it all at the same time. Krisp is an app that can sit between your microphone and any other software on your computer all day – acting as an "artificial audio device" that strips away all audio but your voice before it's routed to whatever software you're using. It doesn't process your audio in post; it works in real time. Its noise-cancelling algorithms can filter out keyboard clicks, people talking in the background, lawnmowers, cars, and most of the noises of everyday life with no audible impact on your own voice. Perhaps the first thing Krisp users will highlight is its artificial noise cancelling for sounds behind the mic – i.e., it can isolate your voice from people talking in the background, a feat most other background noise removers cannot. And in addition, Krisp also implements background noise removal for anything coming into your earpiece on a call, filtering out the background noise coming from the other party. For those looking for even more from their calls, Krisp also offers meeting notes and transcription so the AI can go the extra mile in documenting your calls for you in addition to removing those background noises. With prices ranging from free for individuals with limited features to just $8/month (for the Pro version), Krisp is one of the most affordable tools out there. Perhaps the main caveat to Krisp is that, while background noise cancellation works without an internet connection, some of the AI features can only be utilised while you're online. If taking calls with an imperfect acoustic environment from home, or elsewhere, is something you do with any regularity, Krisp's main benefit is that it eliminates the anxiety that comes from worrying about the external acoustics.

• Category: Audio Editing
• Pricing: Freemium
• Rating: 4.5 / 5 (0 reviews)
• Platforms: macOS, Windows

Key features

• Real-time noise cancellation — Filters background noise from microphone input live before any application captures it
• AI background voice cancellation — Removes other people's voices in your background rather than just steady ambient noise
• Two-way filtering — Cancels noise from both your microphone output and the incoming audio stream from other call participants
• Universal compatibility — Works as a virtual audio device compatible with Zoom Teams Discord Slack and any other app that uses a microphone
• Meeting notes and transcription — AI-generated call notes and transcripts for documentation alongside the noise filtering
• Offline mode — Core noise cancellation functions without an internet connection
• Echo cancellation — Removes acoustic echo from rooms without acoustic treatment
• Low latency processing — Real-time filtering with minimal audio delay suitable for live calls and recordings

Pros & Cons

Pros

• Real-time filtering before capture prevents bad audio from entering the recording rather than cleaning it up after the fact
• AI background voice cancellation that removes other humans talking in your background is a capability most basic noise filters lack
• Two-way filtering that also cleans incoming audio means both sides of the call benefit from noise reduction
• Works as a system-level virtual device compatible with every application on your computer without per-app configuration
• Offline mode for core noise cancellation provides reliability in unstable internet environments

Cons

• Some AI features including certain enhancement modes require an internet connection despite the offline mode for basic cancellation
• Aggressive noise cancellation can clip the beginning of words when you start speaking unexpectedly which creates a brief audio gap
• Pro plan at $8 per month adds up across a year and free alternatives like RTX Voice serve the same core function for Nvidia GPU users
• Meeting transcription accuracy varies significantly with audio quality and accent diversity on multi-participant calls

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