Cleanvoice logo

Cleanvoice

AI audio cleanup for podcasts and voice content that removes filler words, mouth sounds, stutters and background noise with pay-as-you-go credits and simple subscriptions for consistent creators.
audio
Category
Beginner
Difficulty
Active
Status
Web App
Type

What is Cleanvoice?

Discover how Cleanvoice can enhance your workflow

Cleanvoice focuses on speed and clarity: upload your track, choose cleanup options and download a polished result that sounds more professional without hand-editing every second. It targets filler words in multiple languages, trims long silences, reduces mouth clicks and hum, and can de-um speakers while keeping natural cadence. Batch processing helps weekly shows, and an API supports automated pipelines. Pay-as-you-go credits fit occasional users, while monthly/annual plans suit production schedules. Editors often run a quick pass in Cleanvoice before moving to DAW mixing, saving hours per episode. For creators and agencies balancing quality with throughput, it’s a practical first step that reliably removes the most distracting artifacts.

Key Capabilities

What makes Cleanvoice powerful

Filler & Silence Control

Detect ums/ahs and long gaps, then trim and smooth timing so speech flows naturally without robotic pacing.

Implementation Level Basic

Clicks & Room Tone

Reduce mouth clicks, hum and room noise to lift speech intelligibility before EQ and compression in your DAW.

Implementation Level Basic

Batch & API

Process episodes in batches or call the API from your pipeline so recurring shows stay on schedule.

Implementation Level Basic

Credits & Plans

Choose pay-as-you-go credits or subscriptions. Long-valid credits fit occasional use; subs suit weekly production.

Implementation Level Basic

Key Features

What makes Cleanvoice stand out

  • Filler word detection across multiple languages
  • Silence trimming and timeline tightening
  • De-clicking de-hum and room noise reduction
  • Batch processing for series and back catalogs
  • Speaker handling to keep cadence natural
  • Simple web UI plus API for automation
  • Pay-as-you-go credits valid long periods
  • Exports ready for DAW mixing and mastering

Use Cases

How Cleanvoice can help you

  • Weekly podcast cleanup before DAW mixing
  • Webinar and course audio polish
  • Interview fixes for remote recordings
  • Short-form social voiceovers cleanup
  • Client deliverables for agencies at scale
  • Back catalog refresh projects
  • Voice memo to professional narration upgrade
  • Transcription-ready audio preparation

Perfect For

podcasters, editors, educators, agencies and creators who want cleaner speech with minimal effort and predictable cost

Plans & Pricing

Free trial / From €10 per month

Visit official site for current pricing

Quick Information

Category audio
Pricing Model Free trial / credits
Last Updated 3/19/2026

Compare Cleanvoice with Alternatives

See how Cleanvoice stacks up against similar tools

Frequently Asked Questions

Is there a free trial and what is the starter price?
Yes, you can try it free and starter pricing begins around ten euros for a small hours bundle, with larger bundles priced more efficiently.
Will it ruin natural speech cadence?
The system targets filler words and long gaps while keeping timing natural; you can review changes before export.
Does it support multiple languages?
Yes, filler word detection supports several languages, helpful for multilingual shows.
Can I automate processing for a series?
Yes, use batch jobs or the API to process episodes automatically as part of a weekly pipeline.
Do credits expire quickly?
Pay-as-you-go credits typically remain valid for up to two years, which suits occasional projects.
Is this a replacement for full editing?
It’s a cleanup pass that saves hours; detailed editorial cuts still happen in a DAW.
What file types are supported?
Common audio formats like WAV and MP3 are supported for upload and download.
How does it compare to manual cleanup?
It’s far faster for routine artifacts, letting editors spend time on story and mix decisions instead of de-umming.

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