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Filler Word Remover

Automatically cut "um", "uh", and awkward pauses from podcasts, voiceovers, and videos. AI finds every filler with word-level timing and removes it — the result is tighter and shorter.

Removing filler words means cutting the "um"s, "uh"s, and dead pauses out of a recording so the speech flows tighter. EditClips.online does it automatically: AI speech recognition produces word-level timestamps, every filler is matched and cut with a small guard so neighboring words are never clipped, and long pauses are optionally shortened to a natural gap. Upload a podcast, voiceover, or video, click Process, and download the cleaned, shorter file.

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Processed on our servers — requires a free account

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How to Use Filler Word Remover

  1. Upload your podcast episode, voiceover, or video
  2. Choose how aggressively to shorten pauses (Natural is a good default)
  3. Optionally add your personal filler words
  4. Click Process — AI finds and cuts every filler
  5. Preview and download the tightened recording

Features

  • Cuts um, uh, erm, hmm and other fillers automatically — no timeline scrubbing
  • Shortens awkward pauses to a natural gap (or leave them, your choice)
  • Word-level precision with a guard zone so real words are never clipped
  • Add your own verbal tics — "like", "basically", anything you say too often
  • Works on audio (MP3, WAV) and video (MP4, MOV) alike
  • Shows how many fillers were cut and how much time you saved

Frequently Asked Questions

Which filler words does it remove?
The built-in list covers non-word vocalizations: um, uh, uhm, erm, er, ah, hmm, mhm and variants. Meaningful-but-overused words like "like" or "basically" are NOT cut by default — add them yourself in the extra-words field if you want them gone, since cutting them can change meaning.
Will it clip the words around a filler?
No — each cut is clamped against the neighboring words' timestamps with a small guard zone, so the edit points always land in the silence around the filler, not inside real speech.
How much shorter does my recording get?
Typical unscripted speech contains 3-8 fillers per minute plus pauses; a 20-minute podcast episode commonly loses 1-3 minutes. The result page shows exactly how many fillers were cut and the total time saved.
Does it work on video?
Yes — the video is cut at the same points as the audio so everything stays in sync. Video output is re-encoded (cuts require it) at high quality; audio-only files come back as MP3.
Is this like Descript's filler removal?
Same idea — automatic, transcript-driven filler removal — but as a simple browser tool: upload, process, download. No project setup, no subscription required to try it.