Meeting Transcription Accuracy: What Affects It and How to Improve It

Meeting transcription accuracy varies significantly based on conditions that teams can actually control. Understanding what affects accuracy lets you improve it without changing your transcription tool.

The main variables affecting transcription accuracy

• Microphone quality: a dedicated headset or USB microphone produces dramatically better audio than a laptop's built-in microphone in a noisy environment.
• Background noise: keyboard noise, HVAC, and nearby conversations all introduce errors. Noise cancellation at the software or hardware layer reduces this.
• Speaker accents and speaking pace: ASR models are trained on distributions of speech data. Speakers with less common accents or who speak unusually fast may see lower accuracy.
• Domain-specific terminology: technical jargon, product names, and proper nouns are more likely to be transcribed incorrectly than common vocabulary.
• Language specification: if the transcription system is set to auto-detect language and the speaker has an accent from a different language background, the system may make incorrect language assumptions.

How MeetOye improves transcription accuracy

MeetOye's Oya assistant uses English-language models specifically tuned for meeting audio when the meeting language is set to English. For multilingual meetings, the language specification can be set explicitly. The system applies voice activity detection to filter out non-speech segments and uses speaker diarization to segment audio by participant, which reduces the error rate from cross-talk.

Practical steps to improve transcription quality

• Use a headset or dedicated USB microphone instead of laptop audio.
• Enable software noise cancellation if your platform supports it.
• Speak at a moderate pace when sharing important information.
• Set the language explicitly rather than relying on auto-detection.