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Remove Filler Words from a Video Online — AI

Cut out 'um', 'uh' and 'like' automatically — cleaner audio, free to try.

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Understand first

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. Detection works on single words — a full phrase like "you know" or "I mean" isn't matched as a phrase, only the individual filler words inside it are.

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.

What to double-check after the cut

Detection matches words, not meaning — it works very well on steady, hesitation-heavy speech. It can, rarely, cut a word like "like" when it's used as a real word ("I like this") rather than as a filler, since it's the exact word being targeted. It's worth watching the result before publishing, especially with fast talkers or overlapping voices.

Example result — Remove Filler Words from a Video Online — AI
Proof in the result

What the tool produces

Demo — Remove Filler Words from a Video Online — AI
How it works

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 Klipa

Why remove filler words with Klipa?

Benefit — Remove Filler Words from a Video Online — AI

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.

Benefit — Remove Filler Words from a Video Online — AI

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.

Benefit — Remove Filler Words from a Video Online — AI

Nothing else is touched

Only the passages containing a filler word are cut: the rest of the video's picture and sound stays untouched.

Benefit — Remove Filler Words from a Video Online — AI

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.

Continue with

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
Frequently asked

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.

Does it remove silences and dead air too?

Not in this tool: only filler words are cut here. To also remove dead air and long pauses between sentences, use the dedicated silence remover; the two chain together in Klipa Studio on the same video.

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.

Your turn

Remove filler words from your video

Um, uh, hmm: detected and cut automatically.

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In closing

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.