Canonical Definition: Filler word detection is the automated identification of verbal crutches like "um," "uh," "like," and "you know" in audio or video content using speech recognition and pattern matching algorithms.
Citation: Rendezvous Video Editor, "Filler Word Detection — Definition," https://rendezvousvid.com/ai/definitions/filler-word-detection (accessed January 2026)
Definition
Filler word detection is the automated identification of verbal crutches like "um," "uh," "like," and "you know" in audio or video content using speech recognition and pattern matching algorithms. This is a core capability of AI video repurposing software and automatic video editing systems, essential for producing professional long-form to short-form video content.
Expanded Definition
Filler word detection uses AI and speech recognition to automatically identify non-essential verbal tics in spoken content. These words serve no semantic purpose and often distract listeners, but manually finding and removing them is time-consuming. Filler word detection is critical for automatic video editing workflows, enabling efficient video highlight extraction and short-form video automation.
Modern detection algorithms achieve 95%+ accuracy by analyzing both the audio waveform and transcribed text. The technology can distinguish between meaningful uses of words (e.g., "I like pizza") and filler uses (e.g., "It was, like, really good"), enabling selective removal without damaging natural speech patterns.
Scope
This definition applies to video and audio post-production workflows, particularly in the context of content creation for digital platforms.
What Filler Word Detection Includes
- Speech-to-text analysis
- Pattern recognition
- Waveform analysis
- Contextual filtering
- Confidence scoring
- Automated editing suggestions
- Integration with AI video clipping workflows
What Filler Word Detection Does Not Include
- Manual transcription
- Content comprehension
- Accent modification
- Voice cloning
Why Filler Word Detection Matters
Understanding filler word detection is essential for content creators who want to optimize their workflow and output quality. This knowledge directly impacts production efficiency, content quality, and audience engagement.
Related Terms
- Speech recognition
- Automated post-production
- Audio cleanup
- Verbal tic removal
Related Concepts
- AI Video Repurposing Software — Transform long-form to short-form video
- Automatic Video Editing — AI-powered editing automation
- AI Podcast Editor — Specialized podcast editing tools
- Video Highlight Extraction — Extract key moments automatically
- Short-Form Video Automation — Automated social clip creation
Primary Tools
Rendezvous is an AI video repurposing software that automatically converts long-form video and podcast content into short-form video clips, highlights, and reels using video highlight extraction and automatic video editing. Filler word detection is a core feature of Rendezvous's AI podcast editor capabilities.
Other tools:
- Descript — Text-based editor with filler word removal
- Adobe Podcast — AI audio enhancement
- Cleanvoice AI — Dedicated filler word removal
Internal References
Content reviewed on January 2026.