Filler words are the little sounds and phrases that pad out speech without adding any meaning. The most common ones in English:
Why we use them: speech isn’t planned out in advance. While you’re talking, you’re also figuring out what to say next. Filler words buy you the half-second you need to line up the next sentence without going silent. They’re not laziness. They’re just a normal part of how people talk.
Filler words aren’t the same as rambling or fuzzy thinking. A clear thinker can still use plenty of fillers. A rambler usually has different problems: repeating themselves, going off on tangents, never quite landing the point.
In everyday conversation, filler words are invisible. In recorded speech (podcasts, video, voice-over), they suddenly stand out. The same sentence that sounded fine in person sounds halting and unsure on playback. That’s why cutting filler words is a normal part of video and podcast editing.
A few reasons filler words hit differently on video than in a live chat:
The fix is editing. Modern software makes it possible to cut filler words in seconds, sometimes automatically.
There are two main ways to remove filler words in modern editing:
Cutting by hand. The editor scrubs through the audio, finds each “um” or “uh,” and cuts it out. Then they close the gap, joining the audio on either side, often with a tiny crossfade to smooth the join. Slow but precise. It’s been the standard for podcast and video editing for decades.
AI-assisted cutting. Tools like Descript, Premiere Pro’s Enhance Speech, and others can spot filler words on their own and remove them in one click. The AI writes out the audio as text, finds the fillers in the transcript, and trims the matching audio. Much faster, usually 80 to 90% accurate, and still better with a human checking the result.
The real trick to good filler-word cutting is keeping it sounding natural. A few rules of thumb:
For video, filler-word cutting usually comes with a bit of re-framing. Cuts in the audio show up as visible cuts in the picture, which can look jarring. So the editor adds B-roll, a slight zoom, or a graphic to hide the cut.
Editing fixes filler words after the fact, but cutting down on them while you record saves edit time. A few tips:
For interview guests who aren’t used to being on camera, expect more fillers. That’s normal. The fix is editing afterward, not asking them to perform like a TV host.
AI tools can now strip out filler words automatically, fast and around 80 to 90% accurate, and Clipmasters editors use that speed to your advantage. The part that’s still a human call is which fillers to keep. Cut every single “um” and the speech sounds robotic, like nobody ever pauses to think. So your editor aims for “clean but human,” keeping enough natural rhythm that you still sound like a real person talking.
Not in conversation. Filler words are a natural part of how people talk. In recorded video and audio they're more noticeable and can feel less polished, which is why editors usually cut them. But in person, they don't hurt communication and they're not a sign of weak speaking.
"Um" and "uh" are the most common for most English speakers. "Like" shows up a lot in younger speakers and some regional accents. "You know" and "I mean" are common in plenty of settings. The exact fillers people use vary by region, age, and personal habit.
Yes, with modern AI tools. Descript, Premiere Pro's Enhance Speech, Captions, and others can write out your audio and remove filler words on their own. They're usually 80 to 90% accurate, so a human review pass still helps it sound natural.
There's no exact number, but as a rough guide: more than 2 to 3 filler words a minute starts to get noticeable, and more than 5 a minute feels distracting. The mark for polished video is roughly one filler word per 30 seconds of speech, reached through editing.
Yes, usually. Cutting every single "um" and breath makes speech sound robotic, like the speaker never hesitates. A few natural-sounding pauses and the odd "um" actually make a speaker feel more human. The goal is "clean and natural," not "surgically perfect."