Filler Word Counter — Clean Up Your Transcript
Free filler word counter for transcripts and scripts. Private, browser-based, and no upload required.
Default fillers include: um, uh, er, ah, like, you know, basically, literally, actually, honestly, right, so, well, I mean, kind of, and sort of.
Filler Word Overview
Run the filler word counter to find verbal tics, measure filler density, and generate a cleaner transcript.
| Filler | Count | Share of words |
|---|
Highlighted Transcript
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Download MacParakeet — FreeCommon filler words in English conversation
A filler word counter helps you spot the language habits that creep into natural speech. Words and phrases like "um," "uh," "like," "you know," and "I mean" are normal in real-time conversation because they buy a speaker time to think. In live dialogue, that is often fine. In transcripts for blogs, reports, podcasts, or training material, those same fillers can make text feel repetitive and harder to scan.
Most people do not notice how often they use fillers until they see a count. That is why a clear frequency breakdown matters. When you can measure repeated tics by word and percentage, editing becomes objective instead of guesswork. You can decide which fillers to keep for voice and personality, and which ones to remove for clarity.
How filler words affect clarity and credibility
Filler-heavy transcripts slow readers down. Each extra "well," "actually," or "kind of" adds friction, especially in instructional or professional content where precision matters. If you publish interviews, meeting notes, course transcripts, or sales call summaries, cleaner text improves comprehension and makes key points easier to find.
There is also a perception effect. In high-stakes communication, dense filler usage can make delivery sound uncertain even when ideas are strong. Reviewing a report from a filler word counter is a simple coaching tool for speakers, hosts, and teams who want more confident phrasing over time.
Cleaning transcripts before publishing
A practical workflow is: transcribe first, run a filler scan second, then clean text for distribution. This tool supports that process in one pass by showing per-term counts, highlighting matches in context, and generating a cleaned transcript you can copy or download. You can also add custom fillers for speaker-specific habits, which is useful in recurring podcasts or internal training series.
For publication workflows, removing even a small percentage of filler words can noticeably tighten pacing. Paragraphs become shorter, sentences read more directly, and editing rounds move faster because you are not manually hunting for common disfluencies.
Why private, browser-based analysis matters
Transcript data often contains sensitive material: client calls, internal planning, legal interviews, or unreleased product details. This filler word counter runs entirely in your browser, so your text stays on your device. No uploads, no API calls, and no account are required, which makes it safe for quick checks during active editing work.
Frequently Asked Questions
What counts as a filler word?
We detect common speech disfluencies (um, uh, er, ah) and discourse markers often used as fillers (like, you know, basically, literally, actually, I mean, sort of, kind of).
Can I add custom filler words?
Yes. Add your own words to the detection list — useful for catching verbal tics specific to a speaker.
Does MacParakeet remove fillers automatically?
Yes. MacParakeet's clean text pipeline automatically removes filler words during transcription, giving you publish-ready text from the start.