The short answer
Short answer
Use a tool that finds the cuts for you, then review every one before you export. Loudness-based tools such as auto-editor remove silence but cannot tell an “um” from a word. Transcript editors and AI agents remove filler words and long pauses by reading a word-level transcript. Whichever you use, leave a little padding at each cut and keep the pauses that end a thought, or the result sounds robotic.
A few terms used below. Dead air is silence with no purpose, such as the seconds before you start talking. A filler word is a sound or phrase that fills a gap without adding meaning, like “um” or a stray “you know”. A jump cut is a cut within the same shot, which makes the picture visibly jump. A word-level transcript lists every word with its start and end time, which is what lets software cut by words instead of by sound.
What are the ways to remove silence and filler words?
There are four families of method. They differ in how they find a cut, whether they understand words, and how much checking they leave to you.
By hand in any editor
- How it finds cuts
- You listen and cut
- Removes filler words?
- Yes, by ear
- Typical failure
- Slow, and only as consistent as you
Loudness tools (auto-editor, Recut, editor silence tools)
- How it finds cuts
- Audio quieter than a threshold for a minimum time
- Removes filler words?
- No: an um is as loud as a word
- Typical failure
- Clipped word starts, chopped breaths, jumpy picture
Transcript editors (Descript, Premiere text-based editing)
- How it finds cuts
- Word timestamps from a transcript
- Removes filler words?
- Yes, from a word list
- Typical failure
- Misses fillers the transcript left out; harsh cuts
An AI agent in your editor (Rushilo with Claude Code or Codex)
- How it finds cuts
- The agent reads the transcript and cuts by word
- Removes filler words?
- Yes, plus retakes and false starts
- Typical failure
- Can over-cut if you do not say how long pauses may be
| Method | How it finds cuts | Removes filler words? | Typical failure |
|---|---|---|---|
| By hand in any editor | You listen and cut | Yes, by ear | Slow, and only as consistent as you |
| Loudness tools (auto-editor, Recut, editor silence tools) | Audio quieter than a threshold for a minimum time | No: an um is as loud as a word | Clipped word starts, chopped breaths, jumpy picture |
| Transcript editors (Descript, Premiere text-based editing) | Word timestamps from a transcript | Yes, from a word list | Misses fillers the transcript left out; harsh cuts |
| An AI agent in your editor (Rushilo with Claude Code or Codex) | The agent reads the transcript and cuts by word | Yes, plus retakes and false starts | Can over-cut if you do not say how long pauses may be |
What counts as a filler word, and what counts as a pause?
Fillers come in two kinds. Hesitations such as um, uh, er and hmm are never words, so removing them is safe in principle. Discourse words such as like, you know, so and actually are sometimes fillers and sometimes meaning (“I like it”), so a remover has to tell the difference.
They are common. A 2021 paper in Language and Speech, summarising earlier studies, puts filled pauses at about 2 to 6 per 100 words of spontaneous speech. At a typical talking pace that adds up quickly, but it varies a lot between speakers and drops sharply when someone is reading a script.
Pauses are not all the same either. It helps to sort them before cutting:
- Dead air: before the first word, after the last, or while you look at notes. Cut it.
- Thinking pauses: mid-sentence while you find a word. Shorten them.
- Emphasis pauses: just before or after a point you want to land. Keep them.
- Reading pauses: while a chart, number or code appears on screen. Keep them long enough to read.
What settings should you start with?
Short answer
There is no standard pause length, but published defaults give good starting points: auto-editor uses a 0.04 audio threshold and 0.2 seconds of margin on each side of a cut, and Recut says 0.4 to 0.5 seconds of padding sounds natural. Start there, listen, and adjust.
auto-editor
- Setting
- Audio threshold
- Value
- 0.04
- Source
- README
auto-editor
- Setting
- Margin (padding each side)
- Value
- 0.2 s
- Source
- README
auto-editor
- Setting
- Smooth (minimum cut, minimum clip)
- Value
- 0.2 s, 0.1 s
- Source
- Options
Recut
- Setting
- Padding
- Value
- 0.4 to 0.5 s sounds natural
- Source
- Recut guide
Clipchamp
- Setting
- Auto cut
- Value
- Pauses longer than 3 s
- Source
- Clipchamp blog
Rushilo
- Setting
- Pause limit
- Value
- 0.5, 1, 1.5 or 2 s; default 1 s
- Source
- Rushilo transcript panel
| Tool | Setting | Value | Source |
|---|---|---|---|
| auto-editor | Audio threshold | 0.04 | README |
| auto-editor | Margin (padding each side) | 0.2 s | README |
| auto-editor | Smooth (minimum cut, minimum clip) | 0.2 s, 0.1 s | Options |
| Recut | Padding | 0.4 to 0.5 s sounds natural | Recut guide |
| Clipchamp | Auto cut | Pauses longer than 3 s | Clipchamp blog |
| Rushilo | Pause limit | 0.5, 1, 1.5 or 2 s; default 1 s | Rushilo transcript panel |
Recut puts the extreme case well: with no padding, it says, the result sounds “like one of those fast-talker radio ad spots”. For a talking-head YouTube video, a 1 second limit with some padding keeps the rhythm. For short-form, go tighter: Rushilo’s own short-form recipe leaves about 0.4 seconds. auto-editor also has a preview option that shows what it will cut before it changes anything; use it.
Why do automatic cuts sound robotic or choppy?
Four causes account for most of it:
- Cutting at the exact edge of a word. The breath and the first sound of a word often start before the point a detector marks, so a tight cut clips it.
- Removing every breath. People breathe. Without breaths, sentences run into each other.
- Uniform pacing. When every gap becomes the same length, speech loses the rhythm that tells a listener where a thought ends.
- Jumpy picture. A head that moves between sentences jumps at every cut. One creator described the result:
“I keep re-fixing cuts by hand and it kills the time savings.”
Editors in r/editors were blunt about the built-in silence removers that cause this: “That feature was designed specifically to create jump cuts in order to get runtime shorter.” The fix is not to give up on automation, it is to set it up so it leaves room, and to review.
How do you hide jump cuts?
You hide a jump cut by changing the picture at the cut, or by not cutting there at all. The advice from working editors is consistent:
- Punch in. Scale the shot up slightly after the cut, so the jump reads as a deliberate reframe.
- Cover with B-roll or a graphic. Put a screenshot, chart or clip over the join.
- Use another angle if you recorded one.
- Cut ideas, not gaps. One r/editors reply: “Leave natural silence in and cut out concepts and beats instead of every pause.”
- Leave a handle. Another editor’s tip: keep “a short handle on either side of each cut rather than cutting right at the audio boundary.”
Should you remove every um and uh?
No. Removing all of them is the most common way to make someone sound unnatural. Podcasters in r/podcasting put it plainly:
“AI edits that remove 100% of filler don’t sound good!”
Our rule of thumb, drawn from those threads:
- Remove fillers that cause a stumble or make the speaker sound unsure of a fact.
- Keep the ones that pass quickly, the way they would in conversation.
- Leave a filler that runs straight into the next word. As one podcaster put it, cutting those “tends to create an unnatural chop”.
- For short-form video, cut harder; for interviews and podcasts, cut lightly.
Descript builds in the same instinct: its filler word tool has an “Avoid harsh cuts” option that skips fillers it cannot remove without clipping a nearby word.
Will an automatic remover cut real words?
A good one will not touch “like” in “I like it”. One common approach is to check whether the word is set off from the sentence. Rushilo’s remover is a useful example because its rules are simple:
- It always removes hesitations: um, umm, uh, uhh, uhm, er, erm, hmm and mm.
- It removes “like” and “you know” only when they are set off by a comma, the end of a sentence or a pause of 0.3 seconds or more. So it keeps “do you know him?” and removes “it was, like, great”.
- It removes the first of a word said twice in a row (“I I think”).
- It does not remove “so”, “actually”, “basically” or “I mean”.
Every rule has edge cases. A word repeated on purpose, as in “had had”, looks like a stutter. That is why the remover shows how many it found and how many seconds it will take out before anything changes.
How do you remove silence and filler words with Claude Code or Codex?
An AI agent adds judgement to the rules above: it can also find retakes and false starts, which no word list catches. We make Rushilo, a desktop editor that Claude Code and Codex drive, so here is how it works there:
- 1Import your recording and make a transcript, on your computer with Whisper or with your own OpenAI, Groq or Gemini key.
- 2Use Remove filler words or Tighten pauses in the transcript panel, or ask your agent, for example: “Remove ums and retakes, and shorten pauses over one second to about half a second.”
- 3Check the preview: it shows how many it found and the seconds it will remove.
- 4Apply. Each cut closes the gap on every track, and the whole clean-up is one undo step, so you can step back if the pacing feels wrong.
- 5Watch the joins and punch in or cover any that jump.
The limits are worth knowing. Rushilo finds pauses from the gaps between words, not from audio loudness, so it will not find silence in footage with no speech. Its filler list is fixed. And on-device transcription is slower than the fastest native Whisper tools. The full workflow with an agent is covered in how to edit video with Claude Code and how to edit video with Codex.
Frequently asked questions
How do I remove silence from a video for free?
Free options include auto-editor, a public domain command-line tool that cuts by loudness, Clipchamp's auto cut, which removes pauses longer than 3 seconds, and cutting by hand in any free editor. Paid transcript editors and agent workflows add filler word removal and review.
Does removing every um make you sound robotic?
Usually, yes. Podcasters and editors widely report that removing every filler and pause makes a speaker sound like they are reading. Remove the fillers that cause a stumble, keep the ones that pass quickly, and keep pauses that mark the end of an idea.
How long should a pause be before I cut it?
There is no standard. Common starting points are auto-editor's default 0.2 second margin on each side of a cut and Recut's advice that 0.4 to 0.5 seconds of padding sounds natural. Rushilo's pause limit defaults to 1 second. Start there and adjust by ear.
How many filler words does a person say?
A 2021 Language and Speech paper, summarising earlier studies, puts filled pauses such as um and uh at about 2 to 6 per 100 words of spontaneous speech. Scripted or rehearsed speech has fewer. It varies a lot between speakers.
Why does my editor say no filler words were found when I can hear them?
Transcript-based tools only remove what the transcript contains, and speech-to-text models often leave out ums and uhs. If the transcript does not show them, the remover cannot find them, so read the transcript before trusting the count.
Can Claude Code or Codex remove filler words from a video?
Yes, when they drive an editor that exposes a word-level transcript. In Rushilo, the agent reads the transcript, cuts ums, retakes and long pauses by word, and every cut is previewed and can be undone. You need your own Claude Code or Codex plan; Rushilo ships no AI.
Sources
- auto-editor READMEDefault audio threshold 0.04 and margin 0.2 seconds. Read 2026-10-12.
- auto-editor options reference (v31.6.1)Margin, smooth (0.2 s minimum cut, 0.1 s minimum clip) and preview options. Read 2026-10-12.
- Recut: remove silence from video automaticallyPadding of 0.4 to 0.5 seconds sounds natural. Read 2026-10-12.
- Clipchamp: remove silences from videoAuto cut flags pauses longer than 3 seconds. Read 2026-10-12.
- Descript Help: filler wordsDetects um and uh; per-instance review; Avoid harsh cuts. Read 2026-10-12.
- Language and Speech (2021): Can filled pauses be represented as linguistic items?About 2 to 6 filled pauses per 100 words, summarising earlier studies. Read 2026-10-12.
Cite this page
Last verified: Oct 12, 2026
Patel, O. (2026, October 12). How to remove silence and filler words from video without robotic jump cuts. Rushilo. https://rushilo.com/blog/remove-silence-and-filler-words
About the author
Founder, Rushilo
Om Patel is the founder of Rushilo, a desktop video editor driven by the user's own AI, and of BigIdeasDB, a research platform that reads real complaints and reviews to help founders validate products. He writes Rushilo's research articles with the same method: primary sources, dated numbers and the words real users write.
