Filler Words in Other Languages: A Tour of the 8 We Detect

A detector that only knows um and uh is blind the moment you switch languages. Filler words in other languages rarely sound like um: Spanish speakers say este, French speakers say euh, Japanese speakers say eeto, and Arabic speakers say yaani. Detection has to be tuned to each one, or the recording comes back almost untouched.

Why the English list does not travel

Every language has its own set of verbal placeholders, and most of them are real words with real meanings in other positions. Spanish bueno means "good". French donc means "therefore". German also means "so". Japanese ano means "that". A detector that matches on sound alone will either miss these fillers entirely or, worse, cut the word when it is doing real work in the sentence.

That is why TrimTake's detection engine handles each of its 8 supported languages separately: English, Spanish, Portuguese, French, German, Japanese, Hindi and Arabic. The engine listens for the placeholders that speakers of that language actually use, then checks the position and timing of each one before marking it for removal. You see every proposed cut struck through in the transcript before you download, so a borderline case never leaves without your approval. The full process is on the how it works page.

Below is a decision guide: find the language you record in, and you will know what to expect.

If you record in English

Expect um, uh, like, you know, basically, literally, right, so and actually to be the usual suspects. The tricky ones are like, so and right, because each has a legitimate job in many sentences. A good pass removes "it's, like, three bedrooms" and keeps "I like this neighbourhood". If your recordings are heavy on sentence-opening so, start with the Light cleanup level and raise it only if the preview shows cuts you agree with.

If you record in Spanish

Expect este, o sea, bueno, pues, ¿no?, ¿verdad? and básicamente. Spanish fillers tend to cluster at the start of a thought (este, bueno, pues) and at the end (¿no?, ¿verdad?). The tag questions are the ones that quietly erode a sales presentation, because they make every statement sound like a request for reassurance. Note that o sea is two words that behave as one unit, so detection has to treat the pair together rather than cutting half of it.

If you record in Portuguese

Expect então, tipo, né, assim, ã, é and hum. Portuguese has one of the more dangerous overlaps on the list: é is both a filler sound and the verb "is". A detector that strips every é will wreck your grammar. Expect né and tipo to be the most frequent cuts in a coaching call, and então to be the most frequent at the top of a sentence.

If you record in French

Expect euh, ben, voilà, donc, enfin, genre and bah. French speakers lean on euh heavily, often with a long stretched vowel, which means silence removal and filler removal work as a pair here. Voilà and donc are the ambiguous ones: voilà closing a demonstration is useful, voilà dropped mid-sentence as a breath is not. Position decides, and the preview lets you confirm.

If you record in German

Expect äh, ähm, halt, also, quasi, sozusagen and eigentlich. German fillers are longer and more word-like than the English ones, which is exactly why a sound-only detector misses them. Also at the start of an answer is almost always a placeholder. Also in the middle of a logical argument usually means "therefore" and should stay. Halt is similar: as a filler it is a verbal shrug, as a verb it is an instruction to stop.

If you record in Japanese

Expect eeto, ano, maa, nanka, sonou and ee. Japanese placeholders are long and often sit on their own between phrases, so removing them can save a surprising amount of running time in a lesson or product walkthrough. The caution is ano, which also means "that" when it points at something. A good detector reads the words around it before cutting.

If you record in Hindi

Expect matlab, yaani, to, bas, asal mein and the um and aa sounds that cross over from English. Hindi speakers in business settings often mix English and Hindi in the same sentence, so detection has to cope with "matlab, basically, the deadline is Friday". Matlab and yaani both literally mean "meaning", which is why they are so easy to repeat and so easy to miss when you are listening to yourself.

If you record in Arabic

Expect yaani, aah, hmmm, tayyib and eh. Yaani is the heavyweight here, used the way English speakers use "like" or "I mean", and it appears constantly in unscripted explanations. Tayyib ("okay, fine") often opens a new point and works as a verbal reset. Arabic is also a right-to-left language, so the transcript preview and the captions on your 9:16 clips render in the correct direction.

If you switch languages inside one recording

Keep the recording in one primary language where you can. The engine detects the language of the recording and applies the matching filler set, so a lesson that is mostly Spanish with an English product name will be fine. A recording that alternates whole sentences between two languages is the hardest case for any tool, and the preview matters most there. Review the struck-through words before you approve.

What to do next

Whatever language you record in, the workflow is the same: upload the raw footage, let the engine find the placeholders for that language, review the transcript, and download the clean video, the clean MP3 and the captioned clips. The step-by-step version is at remove filler words from video. If you want a quick count of how many fillers you use before cleaning anything, paste a transcript into the free filler word counter. TrimTake is free to start, then $0.99 per video, with monthly plans on the pricing page.

FAQ

Does TrimTake remove filler words in languages other than English?

Yes. It detects and removes fillers in 8 languages: English, Spanish, Portuguese, French, German, Japanese, Hindi and Arabic. Each language has its own filler set, and you review every proposed cut in the transcript before downloading.

Why not just cut every "um" sound in any language?

Because most fillers in other languages are real words. German also, French donc, Portuguese é and Japanese ano all have legitimate meanings in the right position. Cutting by sound alone would damage sentences, so the engine checks position and timing before marking a word.

Do I have to tell TrimTake which language I am speaking?

No. The language of the recording is detected automatically and the matching filler set is applied. Keeping one primary language per recording gives the cleanest result.

Do the captions on clips work in these languages too?

Yes. Captions are available in 90 or more languages, including right-to-left scripts such as Arabic, and they are cut from the cleaned video so removed fillers never appear on screen.