Mavio delivers 95%+ transcription accuracy under standard conditions. If your transcripts are less accurate than expected, this guide will help you identify the cause and improve results.

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Common accuracy issues and fixes

Cause: The transcription model does not know your company-specific terms, product names, or people’s names.Fix: Add terms to your custom vocabulary:
  1. Go to Settings > Transcription > Custom vocabulary.
  2. Add names, acronyms, product names, and technical jargon.
  3. Future transcriptions will prioritize these terms.
Examples: “Kubernetes” (not “Cooper Netty’s”), “Figma” (not “fig ma”), “OKRs” (not “oh cares”).
Cause: Automatic language detection misidentified the spoken language, often when meetings include code-switching or technical English mixed with another language.Fix: Set a default language:
  1. Go to Settings > Transcription > Default language.
  2. Select the primary language of your meetings.
  3. Mavio will still detect language switches but will default to your selection when uncertain.
Cause: Overlapping speech is inherently difficult for any transcription system. When two people talk simultaneously, words get lost.Fix: There is no technical fix for crosstalk after the fact. To prevent it:
  • Encourage “raise hand” behavior in meetings
  • Use the meeting bot (which captures cleaner audio from the platform) rather than mobile recording
  • Edit the transcript manually for critical sections
Cause: While Mavio supports diverse accents well, very strong accents combined with fast speech can reduce accuracy.Fix:
  • Ensure audio quality is high (headset, quiet environment)
  • Add commonly mispronounced terms to custom vocabulary
  • Use cloud mode rather than privacy mode for better accent handling
Cause: Cafe noise, air conditioning, traffic, and other ambient sounds compete with speech.Fix:
  • Use a headset or close-talking microphone
  • Record in a quiet room when possible
  • Use the meeting bot or system audio capture (which bypass the microphone entirely)
  • Enable High quality recording mode for better noise handling
Cause: Phone lines transmit audio at 8 kHz (narrowband), which is half the quality of computer-based audio (16 kHz+). This reduces the detail available for transcription.Fix: Ask participants to join via computer audio instead of dialing in. If phone dial-in is unavoidable, the accuracy reduction is expected and cannot be fully compensated.

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Factors that affect accuracy

FactorImpactYour control
Audio qualityHighUse headsets, quiet rooms
Speaker clarityHighEncourage clear speech
Background noiseHighControl environment
Number of speakersMediumFewer simultaneous speakers helps
Speaking speedMediumNormal pace is best
Technical jargonMediumCustom vocabulary
Accent strengthLow-MediumCustom vocabulary helps
LanguageLowMost languages well-supported
Recording methodMediumBot and system audio are cleanest

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Improving accuracy over time

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Custom vocabulary

The single most impactful improvement for domain-specific accuracy. Add:
  • People’s names (especially unusual spellings)
  • Company and product names
  • Acronyms and abbreviations
  • Industry-specific terms

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Speaker corrections

When you correct speaker labels, Mavio improves future voice matching. This indirectly improves transcription because correctly attributed audio segments can be processed with speaker-specific acoustic models.

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Transcript edits

Edited transcript segments help Mavio learn which terms are important in your context. While Mavio does not retrain models on individual edits, the system uses edit patterns to inform future vocabulary weighting.

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Reprocessing a transcript

If you have added custom vocabulary or believe a transcript could be improved:
  1. Open the meeting.
  2. Click the three-dot menu > Reprocess transcript.
  3. The transcript is regenerated using the latest models and your custom vocabulary.
  4. Reprocessing takes 2-5 minutes depending on recording length.
Reprocessing replaces the existing transcript. Any manual edits you made will be lost. Export or copy your edits before reprocessing if you want to preserve them.

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When to expect lower accuracy

Some scenarios inherently produce lower accuracy. This is expected and not a bug:
  • Large group brainstorms with frequent crosstalk (many voices overlapping)
  • Recordings in noisy outdoor environments (wind, traffic)
  • Very long meetings (3+ hours) — fatigue in speakers leads to less clear speech
  • Low-bandwidth phone dial-ins — narrowband audio limits accuracy
  • Privacy mode — on-device models are slightly less accurate than cloud models
For critical meetings where accuracy matters most, use the meeting bot with cloud processing, ensure participants use headsets, and add relevant terms to your custom vocabulary before the meeting.