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Cleanvoice AI

Audio Cleaning

Stop editing silence and filler words by hand. Automatically remove “uhs”, “ums”, stuttering, and mouth sounds from your audio recordings instantly.

Clean Audio ↗

About Cleanvoice

Cleanvoice is an artificial intelligence tool designed to streamline the podcast editing process. It detects and removes filler words (like “um”, “ah”), stuttering, dead air, and annoying mouth sounds (clicking/smacking) automatically, saving editors hours of manual work.

How to Use

  1. 1. Upload your audio file (MP3, WAV, M4A)
  2. 2. Select cleaning preferences (e.g., remove stuttering)
  3. 3. Wait for the AI to analyze the track
  4. 4. Review the edits in the browser player
  5. 5. Export the audio or an edit timeline for your DAW

Key Features

🚫 Filler Remover
👄 Mouth Sounds
🎼 DAW Export

Related Tools

D

Descript

Text-based Audio Editor

A

Adobe Podcast

Speech Enhancement

Additional Information

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Use Cases

Cleanvoice is primarily used by podcasters and interviewers who want to sound professional without spending hours manually cutting out “ums” and “ahs.” It is also useful for webinar recordings and voiceover cleanups.

Multitrack Support

A standout feature is Multitrack Support. If you record multiple guests on separate tracks, Cleanvoice keeps the edits synchronized across all files to ensure the conversation stays in time and phasing issues are avoided.

Export to DAW

For professional editors, Cleanvoice allows you to export an EDL (Edit Decision List) or markers. This means you can import the “cut instructions” into Adobe Audition, Premiere, or Audacity to fine-tune the edits non-destructively.

Mouth Sounds & Stuttering

Beyond standard filler words, the AI is trained to detect specific audio artifacts like lip smacking, clicking, and stuttering, which are notoriously difficult to remove manually.

Language Support

The algorithm works with multiple languages (including German, French, and Hebrew) and is designed to handle various accents without accidentally cutting off actual words.