How to Remove Filler Words from Audio

To remove filler words from audio, upload the file so the detection engine can transcribe every spoken word with word-level precision, flag the filler words, and cut them automatically — no video track required.

Audio-Only Cleanup Is Its Own Use Case

Not every recording that needs cleanup has a picture attached. Voiceovers for training modules, podcast episodes, narrated presentations, and phone-recorded client calls are all audio-first, and they carry the exact same "um," "uh," and "like" problems that video recordings do — sometimes more, since there is no visual polish to distract from a rough vocal take.

Why Word-Level Detection Matters for Audio Especially

With no video to reference, the only signal available is the audio itself, so precision matters even more here than in a video pass. A detection engine that reads the actual transcript — rather than just scanning for waveform shapes — catches filler words regardless of tone of voice, pacing, or recording quality.

Step-by-Step

1. Record your audio at a normal, unscripted pace
2. Upload the file — audio or video formats both work through the same flow
3. Choose Medium mode for standard filler word density
4. Review the transcript, where every flagged word appears with strikethrough
5. Download the cleaned audio

What Gets Removed

The audio cleanup feature targets um, uh, uhh, umm, like, basically, literally, right, actually, you know, and I mean — the same filler word set covered on the video side, applied directly to standalone audio.

Where This Matters Most

Course creators recording voiceover narration, consultants recording audio-only client updates, and anyone producing narrated training material benefit from a clean pass before publishing — the difference between a rough first take and a polished final file is a single upload, not a re-record.

Clean video in 9 minutes or it's free. Upload your audio to see it flagged in the transcript, or check pricing for plans starting from $9/mo.