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• How accurate is the audio-to-text conversion for noisy meetings with several speakers or strong accents?

  SaaS Browserからの質問 · 2026年11月5日

  MindNoteのTomya Mateoさんが回答 · 2026年11月5日

  MindNote processes audio-to-text conversion through 2 primary workflows depending on the use case:
  real-time dictation/live meetings and pre-recorded audio or video file uploads (supporting MP3, WAV, M4A, AAC, OGG, OPUS, FLAC, WEBM, AMR, WMA, AIFF, MP4, and MOV up to 500 MB). 

  It delivers fair accuracy in noisy environments, but of course there is room for improvement. So far, has been tested against live lectures and TV content. 

  There are some limitations, single microphone dictation setups present physical limits when separating overlapping voices, labeling speakers chronologically by timestamp instead. 

  Conversely, native virtual meeting integrations (such as Zoom, Microsoft Teams, Slack, and Google Meet) track separate audio streams to label speakers individually with high precision. 

  Offline file uploads take slightly longer to process, but leveraging pre-recorded files enables deeper contextual transcription and cleaner output formatting. 

  Speaking clearly in quiet settings remains the recommended best practice, though built-in AI prompt editing allows instant reformatting of any minor discrepancies.

  I would suggest you to try it, there is a 3 days free trial, and you can check if it works well for your files. 

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