Automatic removal of filler words
A
Abe Dearmer
Hi Jason, thanks for the suggestion. Automatic filler word removal (like “um,” “uh,” “you know”) could definitely make polishing videos faster.
To understand what you’re looking for and scope this properly, can you share a bit more?
1) Where should this live in Sendspark: during recording, after recording in an editor, or as an optional “enhance” step before sharing?
2) Which filler words should be targeted, and should users be able to customize the list?
3) Should the removal be automatic by default, or a review mode where you can approve each cut?
4) How should we handle the gaps: hard cut, auto-tighten with a small crossfade, or replace with room tone to keep it natural?
5) Do you need this for all videos, or mainly for specific use cases like sales outreach, support, or internal updates?
6) Any constraints around accuracy, languages, or accents we should plan for?
If you can also share a short example clip (or typical video length and audio quality), that would help us estimate feasibility and the best approach.