Remove ums, ahs, and filler words from audio
Upload an audio or video file and AI automatically removes filler words (um, uh, like, you know) for a cleaner, more professional recording.
The Filler Word Remover uses AI to detect and remove filler words from audio and video recordings. Upload a recording and the AI identifies filler words — um, uh, ah, like, you know, so, basically, actually, right, and more — and removes them cleanly without leaving awkward gaps or choppy edits. The surrounding audio is smoothly joined for natural-sounding results. Preview the cleaned audio before exporting. Supports both audio files (MP3, WAV, M4A) and video files (MP4, MOV, WebM). Choose which types of fillers to target.
Concrete advantages that save you time and effort.
Seamless removal without gaps, clicks, or choppy edits
Context-aware detection distinguishes fillers from legitimate word use
Customizable filler targeting — choose which types to remove
Preview cleaned audio before exporting for quality control
Supports both audio and video files with audio-only editing
Real-world scenarios where this tool saves hours of work.
Clean up podcast recordings for professional-quality episodes
Polish recorded presentations before sharing with audiences
Edit lecture recordings for clearer student learning materials
Clean meeting recordings for easier review and transcription
Improve video content audio for YouTube and social media
Prepare clean audio tracks for voiceover and narration work
Watch your content flow through each processing stage.
Every speaker uses filler words. Um, uh, like, you know, so, basically, right, actually — they are natural parts of speech. But in recorded content, they undermine professionalism and listener attention. A podcast peppered with ums sounds amateur. A presentation recording filled with you knows distracts from the content. A meeting recording cluttered with fillers is hard to follow. The Filler Word Remover cleans all of this up automatically.
Upload your recording and the AI identifies every filler word with millisecond precision. It does not just detect them — it removes them cleanly. The surrounding audio is cross-faded seamlessly so there are no awkward gaps, clicks, or choppy cuts. The result sounds like the speaker simply never said the filler words. Natural pauses are preserved. Sentence rhythm remains intact.
The detection is sophisticated. The AI distinguishes between 'like' used as a filler ('I was, like, going to the store') and 'like' used as a verb ('I like this approach'). It understands context, not just words. This means legitimate uses of words that can also be fillers are preserved.
Customization puts you in control. Target specific filler types — maybe you want to remove ums and uhs but keep filler phrases like 'you know.' Or maybe you want to remove everything. Set your preferences and the AI adjusts.
Preview is essential and included. Listen to the cleaned audio before exporting. Compare the original and cleaned versions side by side. If the AI removed something you wanted to keep, adjust and regenerate.
For podcasters, this is a post-production game changer. Instead of manually editing out every um (which can take longer than the recording itself), upload and clean in minutes. For educators recording lectures, this produces polished content from raw recordings. For professionals recording presentations, this makes every recording sound rehearsed and confident.
Both audio and video files are supported. For video, the audio track is cleaned while the video remains untouched. The output is a clean video file with all the filler words removed from the audio.
Supported formats include MP3, WAV, M4A, MP4, MOV, and WebM.
Um, uh, ah, like, you know, so, basically, actually, right, and more. Fully customizable.
No. The AI smoothly cross-fades the audio around removed fillers for seamless results.
Yes. Select specific filler types to target and keep others.
Yes. The AI uses context to detect when a word is used as filler versus its legitimate meaning.
Yes. Compare original and cleaned versions side by side before exporting.
Yes. For video files, the audio is cleaned while the video remains untouched.
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