How to Remove Filler Words From a Video With AI

To remove filler words from a video, find each "um", "uh" or "like", cut the short stretch and close the gap, or let an AI tool do the finding and cutting and then check the joins. Cutora AI (usecutora.com), an AI video editor for talking-head creators, cuts clear "um" and "uh" sounds. It keeps words such as "like" and "you know", because those are real words that are often part of the sentence.

What counts as a filler word?

Two groups matter. One is hesitation sounds, "um" and "uh", which carry no meaning and are safe to cut. The second is filler words, "like", "so", "you know", "basically", which sound empty in one sentence and carry meaning in the next. A tool that cuts the second group by rule will sometimes cut a word you needed.

How do you remove them by hand?

1. Play through the recording with a transcript or the waveform visible.
2. Mark the short stretch of each hesitation sound.
3. Delete it and close the gap, so the timeline ripples up.
4. Play the join. If the next word sounds clipped, move the cut a few frames earlier.
5. Leave a natural beat where a breath belongs; removing every beat makes speech sound rushed.

This is accurate and slow. On a long recording the listening is the cost.

How does an AI tool do it?

The tool transcribes the recording, finds the hesitation sounds and the words from its filler list, and cuts them. The quality depends on what it can hear: a sound the speech model did not transcribe, such as a short "uh" between two words, can stay in.

Several tools state filler-word removal on their own pages, among them Gling, Descript and TimeBolt, read on the dates in our comparison pages. Cutora AI cuts clear "um" and "uh" sounds and keeps real words; it also removes long pauses, false starts and repeated takes in the same pass, and you can undo any single cut in the edit list.

What should you check after an automatic cut?

• The word after each cut. A cut that lands late clips the start of the next word.
• Words you chose on purpose. A "you know" before a key point may be intended.
• The rhythm. Removing every hesitation can leave a speaker sounding rushed; keep a beat where the sentence needs one.

Why do filler words appear at all?

Most filler words fill thinking time. A speaker who has not decided the next phrase reaches for a sound that holds the turn. That is why they cluster at the start of a sentence, before a number or a name, and after a question. Knowing this changes how you record: the cure is a planned pause, not a rushed sentence.

How do you say fewer of them while you record?

• Know the opening words of each sentence. The "um" almost always sits in front of the opening word. A short note of each opening is enough.
• Pause instead. A silent beat is easier to cut than a sound, and a viewer hears it as thought, not hesitation.
• Slow down on names and numbers. These are the places where a hesitation sound is most likely, and where a wrong word is most costly.
• Say the sentence again after a stumble. Restart from its opening word. The clean version then follows the stumble, and the stumble is easy to find and remove.

What does an automatic tool leave in?

An automatic tool removes what it can recognise. A short "uh" that the speech model did not transcribe, a filler word that is part of the sentence, and a hesitation inside a word can all stay. That is why the check after the cut matters: play every join, and restore anything you wanted.

Cutora AI cuts clear "um" and "uh" sounds that sit between words. It does not remove words that are real words in a sentence, in English or in Arabic: for example it keeps "like" and "you know" in English and "يعني" in Arabic. If you want those gone, cut them by hand on the timeline, where every cut has an undo.

How do you check the result?

1. Play the cut from the start at normal speed.
2. Stop at each join and listen for a clipped opening word.
3. Compare the length with the raw recording: a big difference in a speech with few pauses is a sign that something was removed that you wanted.
4. Export, and listen once on headphones, because a cut that hides in a speaker is audible in earphones.

Related pages

See also how to remove pauses from a video, removing ums and fillers and which take the first cut keeps.

Frequently asked questions

Does Cutora AI remove "like" and "you know"?

No. It cuts clear "um" and "uh" sounds and keeps words such as "like" and "you know".

Can I undo a filler-word cut?

Yes. Every cut is in the edit list with a restore button, and the whole first cut undoes as one step.

Does it work in other languages?

Captions are English, with Arabic in Beta. Check a short clip of your own language before you rely on the filler cuts.

Why does an automatic cut sometimes leave an "uh" in?

The tool can only remove what the speech model heard. A very short "uh" between two words may not appear in the transcript, so it stays in. Check the joins after the first cut.

Should I remove every filler word?

Not necessarily. Removing every hesitation can leave a speaker sounding rushed. Keep a beat where a sentence needs one, and keep words you said on purpose.