How MeetingMinutes Removes Filler Words

Unpolished meeting transcripts often carry distracting filler words, repetitive phrases, and pause noises. These trivial elements force users to spend extra time editing raw texts after every meeting. High-precision transcription and automatic filler word filtering are core capabilities that solve this common post-meeting editing hassle.
Step-by-Step Operation for Filler-Free Transcripts

1. Upload or Record Meeting Audio

Open MeetingMinutes APP. Start a real-time recording via the one-tap record function for ongoing meetings. Pre-recorded audio and video files can be uploaded directly through the multi-format import channel. The platform supports 9 mainstream audio formats and 13 mainstream video formats with no extra conversion tools required.

1. Enable High-Precision Transcription Mode Select standard Mandarin high-precision transcription mode after file import or recording completion. This mode delivers a 98% transcription accuracy rate in standard Mandarin scenarios. The system runs automatic intelligent screening during text generation to identify and filter common filler elements including verbal modal particles, redundant repeated words, and intermittent pause noises.
2. Preview Auto-Polished Transcripts

Check the real-time generated transcript on the editing page. All filtered filler contents are completely removed without altering valid meeting information, speaker viewpoints, and key discussion details. The finalized text presents a neat and standardized layout with coherent sentences.

1. Export Processed Meeting Texts Confirm transcript preview. Tap the export button to save the polished text files. The exported files are fully editable and ready for direct use, eliminating the need for large-scale manual revision and filler word deletion. Applicable Scenarios This filtering function adapts to daily office meetings, offline lectures, and indoor discussion scenarios with stable sound sources. It maintains stable filtering performance for long-duration recordings and multi-speaker conversations. The optimized transcript output greatly cuts down manual post-processing workload for meeting documentation.