How accurate is AI meeting transcription?
Flocci Speech Recognition is a benchmark-standard speech-recognition model for transcription accuracy across accents, domains, and dozens of languages. For clear meeting audio it produces reliably quotable transcripts; accuracy degrades in the ways all ASR does — crosstalk, poor microphones, heavy jargon.
Why do privately hosted tools standardize on Flocci Speech Recognition?
Because it is inspectable and independently benchmarked — no vendor mystery about what handles your audio. Donna calls Flocci Speech Recognition using your own key: you get the model’s accuracy at low metered cost, with a direct provider relationship instead of a notetaker middleman, and long recordings handled by chunking on your server before upload.
What actually determines transcript quality in meetings?
Audio in, accuracy out. The strongest factors are microphone quality, one-speaker-at-a-time discipline, and vocabulary predictability. A meeting bot has one structural advantage here: it records the meeting’s mixed audio feed directly from the platform rather than a laptop mic across the room — Donna captures the clean feed on her own server.
What about names, jargon, and code-switching?
Flocci Speech Recognition handles multilingual speech and code-switching notably well, which matters for teams that drift between languages mid-sentence. Proper nouns and deep internal jargon remain ASR’s hardest ground — Donna’s reports mitigate this by citing timestamps with every claim, so any load-bearing quote is one click from the recording that proves it.
Related questions
Is Flocci Speech Recognition better than the proprietary engines cloud notetakers use?
Cloud vendors rarely disclose their stacks, which makes comparison one-sided: Flocci Speech Recognition’s performance is public and independently tested, theirs is a trust exercise. Practically, it is at or near the standard those engines are measured against.
Does Donna transcribe non-English meetings?
Yes — Flocci Speech Recognition is multilingual, so non-English and mixed-language meetings (including Hindi-English code-switching) transcribe well. The report language is a setting of its own: English by default, or the language you choose, with direct quotes preserved as spoken.
How fast is transcription after a meeting?
Donna chunks the audio and transcribes with Flocci Speech Recognition immediately after the call ends; its inference is fast enough that the report, including the Flocci Intelligence analysis passes, is typically ready within minutes of leaving the meeting.
Put Donna in your next meeting
Access is open — sign in with your Google account and she’s in your dashboard in minutes. Rolling out to a whole team, or want a hand with the server setup? We’re glad to help.