Definition
Filler word removal is an AI-powered audio editing technique that automatically identifies and removes verbal fillers — such as 'um', 'uh', 'er', 'like', 'you know', 'basically', 'actually', 'sort of' — from spoken content. The AI must not only detect the filler sounds but also cleanly remove them while maintaining natural speech rhythm and avoiding awkward audio artifacts. This technique is particularly valuable for podcasts, interviews, lectures, and talking-head videos where verbal fillers can undermine professionalism and viewer retention.
How Loopdesk Uses This
Loopdesk automatically detects and removes filler words as part of the AI rough cut generation process. The speech-to-text engine identifies fillers contextually — understanding the difference between 'like' as a filler ('I was, like, totally surprised') and 'like' as a meaningful word ('I like this approach'). You can control which fillers are removed and review each removal before finalizing your edit.
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Related Terms
Silence Removal
Automatically detecting and removing silent pauses, dead air, and awkward gaps from video and audio recordings.
Speech-to-Text (ASR)
AI technology that converts spoken language in audio and video into written text, enabling transcription, captioning, and search.
Automated Editing
Software-driven editing workflows that automatically perform tasks like cutting, trimming, transitions, and color matching without manual input.
Rough Cut
The first assembled edit of a video, containing the basic structure and sequence of clips before fine-tuning.