Is this standardizing voices?
No. It doesn’t alter voices permanently or require behavior changes. It’s built to reduce friction in live conversations, not enforce norms.
How does Accent Understanding work?
Accent Understanding runs fully on-device (CPU-only), using a proprietary neural model trained on hundreds of thousands of hours to deliver voice-preserving accent neutralization in near real time (≤200ms). It works instantly across Zoom, Teams, Meet, and other voice conferencing platforms with zero integrations via Krisp’s virtual audio layer.
Does this work for all accents?
Models are trained across diverse English accents and designed to improve intelligibility in global meetings, delivering strongest results across Indian, Filipino, Latin American, African, and Chinese-Mandarin accents, while improving comprehension across many others. Coverage continues to expand.
Will it add latency?
It’s designed for near real-time use (around ~200ms or less), so it should feel natural in conversation.
Will other people hear the “adapted” audio?
No. It’s only for the listener who turned it on.
What about privacy and data use?
Audio is processed on the user’s device in real time. Conversations are not stored or sent to external servers.
Can it misinterpret words or change meaning?
It’s designed to preserve meaning and the speaker’s identity while improving intelligibility. Like any audio tech, results depend on input quality, and you can always toggle it off if it isn’t helping in a specific moment.
Didn’t Krisp already release accent technology?
This is different. It builds on Krisp’s earlier accent AI work, but solves a completely different problem. Accent conversion is outbound, changing how one person sounds to everyone else. Accent Understanding is listener-side and inbound, adapting speech only for the individual listener, locally and in real time. With the addition of Accent Understanding, Krisp now addresses both sides of the conversation, extending real-time voice AI from speech clarity to comprehension, setting a new benchmark for inclusive, comprehension-first voice technology.