Key features
- Filler removal: APAC um/uh/tongue clicks/lip smacks automatically removed
- Dead air compression: APAC long pauses shortened to configurable target length
- Mouth noise removal: APAC background clicks and breath sounds cleaned
- Stutter detection: APAC repeated words and sound repetitions cleaned
- Multi-speaker: APAC per-speaker processing for interview podcast formats
- API access: APAC programmatic audio cleaning for content workflow automation
Best for
- APAC podcasters, voice-over artists, and content teams producing regular audio content who want to automate the most time-consuming cleanup phase without manual audio editing — particularly APAC creators recording in non-professional environments where filler sounds and background noise are unavoidable.
Limitations to know
- ! Single-purpose: APAC cannot replace full podcast DAW for complex editing and mixing
- ! APAC heavy accent filler patterns may require threshold calibration to avoid over-removal
- ! Usage-based pricing accumulates for APAC high-volume production (hours of audio/week)
About Cleanvoice AI
Cleanvoice AI is a specialized AI audio cleaning service that automatically removes filler sounds, mouth noises, dead air, stuttering, and background clicks from APAC podcast and voice recordings — providing a single-purpose upload-and-receive workflow where APAC podcasters submit raw audio files and receive professionally cleaned versions within minutes. APAC creators who record content regularly but spend excessive time on audio cleanup use Cleanvoice to automate the tedious editing phase.
Cleanvoice's filler word detection goes beyond basic 'um' and 'uh' removal — the AI identifies and removes tongue clicks, lip smacking, throat clearing, and breath sounds that conventional audio editors must hunt manually through waveforms. APAC podcast editors spending 3-4 hours per episode on cleanup use Cleanvoice to reduce that phase to under 30 minutes by handling the most time-consuming audio artifacts automatically.
Cleanvoice's dead air removal identifies extended silences in recordings — pauses longer than configured thresholds are shortened or removed, tightening episode pacing without manual cutting. APAC podcast hosts who record with frequent thought pauses use dead air removal to produce more engaging episodes that maintain listener attention without completely eliminating natural speech rhythm.
Cleanvoice processes multi-speaker APAC podcast recordings — handling two-person interview podcasts where each speaker has different filler patterns, accent characteristics, and noise profiles. The AI detects per-speaker audio issues rather than applying global filters, producing better results for APAC mixed-nationality podcast teams (English host + Japanese guest, Mandarin host + English expert) than single-model noise reduction.
Beyond this tool
Where this category meets practice depth.
A tool only matters in context. Browse the service pillars that operationalise it, the industries where it ships, and the Asian markets where AIMenta runs adoption programs.
Other service pillars
By industry