Remove Filler Words From Video Without Re-Recording
You’ve just finished recording a 12-minute video for your YouTube channel. The content is solid, your energy is good, but as you watch the playback, you hear ‘um’…
Spotted in the transcript, cut so you won't hear it
Removing filler words from a video means finding every "um", "uh" or verbal tic in the transcript and cutting it out along with a brief silence around it, so the sentence stays fluid. The result: a clean delivery, without listening back to the whole video to hunt down every hesitation by hand.
Which filler words get caught?
The tool transcribes the video first, then compares every word against a list of common hesitations: um, uh, like, ah… in English, and euh, hum, bah… in French.
A cut you don't hear
Each filler word is removed with a small margin of silence around it, and cuts that land too close together are merged into one to avoid a choppy edit. The sentence keeps its natural rhythm: you hear continuous speech, not a string of jump cuts.
Proof in the result
What the tool produces
How to remove filler words from a video
Step 1
Upload the video
Drop the video file you want to remove filler words from (MP4, MOV, AVI, MKV, WebM, up to 2 GB).
Step 2
Run the detection
AI transcription spots every filler word — um, uh, like… — and cuts it with the silence around it.
Step 3
Download the clean video
Get a video with a clean delivery, ready to publish or to move on to the next editing step.
Why remove filler words with Klipa?
Detection by transcript, not by ear
The AI transcribes the video, then spots every filler word in English and French, so you don't have to relisten to every sentence to catch them.
Smooth cuts, never choppy
Every cut keeps a margin of silence and nearby cuts get merged, so the sentence keeps its natural rhythm to the ear.
Nothing else is touched
Only the passages containing a filler word are cut: the rest of the video's picture and sound stays untouched.
Online, nothing to install
No editing software to open: upload the video in your browser.
Real cases
When to remove filler words
Clean up an interview or video podcast
A guest's hesitations make listening painful: removing them gives a smooth exchange without re-recording anything.
Tighten up a training video
A trainer who piles up "ums" loses the room: removing filler words tightens the explanation without changing its substance.
Prep long-form footage before cutting clips
Speech without filler words yields punchier short clips once you cut them from the cleaned-up version.
Polish a product demo or software walkthrough
A live screen recording narrated on the fly tends to collect hesitations; removing them makes the demo sound more professional without a full re-record.
Clean up a keynote or recorded talk
A webinar or talk recorded in one take often keeps its verbal tics; removing them before it goes out makes the delivery sound more confident.
Related Tools
PrepareFetch the video and get the right format
EditCut, clean the sound and the silences
TransformTurn it into short clips, ready to publish
EnrichSubtitles, translation and transcription
Removing filler words — frequently asked questions
How do I remove filler words from a video?
Upload the video: AI transcription spots every filler word (um, uh, like…) and cuts it along with a small margin of silence, so the edit sounds natural. The rest of the picture and sound is never touched. You then download the clean video, ready to publish.
Which filler words does it catch?
The tool matches common hesitations word by word: in English (um, uh, like, ah…) and in French (euh, hum, bah…). Detection works on single words, not on full phrases like "you know" or "I mean".
Are the cuts audible?
No. Each filler word is removed along with a small margin of silence around it, and cuts that land too close together are merged into one to avoid a choppy edit. You hear a continuous sentence, not a string of jump cuts.
Could it cut a real word by mistake?
Rarely, yes: detection matches a word list, not the meaning of the sentence. "Like" used as a real word ("I like this") is the main risk, since it's the exact word being targeted as a filler. It's worth checking the result before publishing.
Which video formats are accepted?
MP4, MOV, AVI, MKV and WebM, up to 2 GB per file — plenty for a full episode or a whole talk. The clean video is delivered as MP4, with picture and sound unchanged outside the cut passages.
What happens if my video has no filler words?
It's returned to you unchanged, with no cuts at all. Processing doesn't fail either way: you simply get your original file back, ready to download, with no needless cutting and no time lost retrying.
Do I still need Premiere Pro or other editing software for this?
No. Everything happens online in the browser, without opening any editing software or starting a project: upload the video, the AI transcribes it and cuts the filler words, and you get the clean file back directly.
What's the difference between this and a silence remover?
The filler word remover targets verbal hesitations (um, uh, like…); the silence remover targets dead air between sentences, whatever caused it. If a recording is mostly full of verbal tics, start with filler words; if it has long silent gaps, start with the silence remover.
Remove filler words from your video
Um, uh, hmm: detected and cut automatically.
Get started
No credit card required
A clean delivery, without re-recording
Removing filler words from a video by hand means listening to every sentence and cutting at the right spot. Klipa transcribes the video, spots verbal tics in English and French, and cuts them automatically — you just check the result, never re-record the whole thing.
