Filler word removal

The technique starts from a word level transcript. Each word has a start and end time, so the editor can find fillers, mark their exact span, and remove those frames from both the picture and the audio. Silence removal works the same way on the gaps between words, cutting any pause longer than a set threshold down to a short natural breath.

It matters most in short form because the first seconds decide whether a viewer stays. A clip that opens on a pause or an um loses people before the point arrives, and a 45 second clip with a dozen small hesitations can feel slow even when the content is strong. Tightening the speech is one of the cheapest ways to improve pacing without changing what was said.

The nuance is that not every pause is a mistake. A pause before a punchline, a breath before a big claim, or a laugh between two people often carries the moment. Removing every gap produces speech that sounds rushed and robotic, and each cut is a jump in the picture that may need a zoom or a cutaway to hide it. The goal is fewer distractions, not zero silence.

In a clipping workflow it runs after the moment is chosen and before captions are styled, because the captions follow the tightened timing. In Crayo, Remove filler words and Remove silences are optional layers in AutoClip and Edit with AI, and the result opens in the timeline editor for any fixes.