Cleanvoice AI
Cleanvoice is an AI audio editing tool that automatically removes filler words, stutters, mouth sounds, and long silences from podcast recordings and voice cont
What is Cleanvoice AI?
Cleanvoice AI is an audio editing tool that uses machine learning to automatically detect and remove common speech imperfections from voice recordings. It targets filler words such as 'um' and 'uh', stutters, mouth clicks and breathing sounds, and extended silences. The tool is designed primarily for podcast creators, voice-over artists, and anyone producing spoken audio content who wants to improve audio quality without manual editing. Rather than requiring you to listen through entire recordings and make cuts by hand, Cleanvoice processes your audio file and handles these repetitive editing tasks automatically. The tool operates on a freemium model, allowing users to try the service before committing to a paid plan.
Key Features
Automatic filler word removal
detects and removes common speech fillers like 'um', 'uh', 'like', and 'you know'
Stutter and repetition removal
identifies and removes stuttered words and repeated syllables
Background noise reduction
cleans up mouth clicks, breathing sounds, and other vocal artifacts
Silence trimming
automatically shortens or removes extended pauses and dead air
Batch processing
allows you to process multiple audio files at once to save time
Audio format support
works with common audio formats used in podcasting and voice production
Pros & Cons
Advantages
- Saves significant editing time by automating tedious audio cleanup tasks
- No special audio editing skills required; the process is straightforward and accessible
- Free tier lets you test the tool on real recordings before paying
- Fast processing means quick turnaround on edited audio files
Limitations
- Automated removal may occasionally cut dialogue that should have been kept, requiring manual review
- The quality of results depends on original audio quality; very poor recordings may need separate cleanup first
- Free tier likely has limitations on file length or processing frequency that may not suit high-volume creators
Use Cases
Podcast creators cleaning up host and guest audio before publishing episodes
Voice-over artists preparing professional recordings for audiobooks or commercial work
Interview-based content creators removing stutters and filler words from recorded conversations
YouTube creators improving audio quality of voiceover tracks
Transcription services cleaning audio before processing to improve accuracy