Cleanvoice utilizes artificial intelligence to automatically remove filler words, stutters, and mouth sounds from audio recordings, streamlining the podcast editing process. This technology enables podcasters to save significant time by enhancing audio quality without the need for manual editing.
Funding
Funding not disclosed
Founders
Product
Problem
Podcast editing is a time-intensive process, requiring meticulous manual removal of filler words, stutters, mouth sounds, and background noise. This process can be especially burdensome for independent podcasters and content creators with limited time and resources. Traditional audio editing software often has a steep learning curve, further complicating the process.
Solution
Cleanvoice AI offers an automated solution that streamlines podcast post-production by using artificial intelligence to identify and remove unwanted elements from audio recordings. The platform automatically eliminates filler words, stutters, mouth sounds, background noise, and long pauses, significantly reducing editing time. Users can upload audio or video files, and Cleanvoice AI processes the files to deliver a cleaner, more professional-sounding recording. In addition to audio cleanup, Cleanvoice AI provides transcription and summarization features, allowing users to generate transcripts, show notes, and social media content from their podcasts.
Target Audience
Cleanvoice AI targets podcasters, video content creators, and audio professionals who want to save time and improve the quality of their recordings without extensive manual editing.
Features
- AI-powered removal of filler words (e.g., "um," "ah," "you know") in over 20 languages
- Automatic detection and removal of mouth sounds, lip smacks, and breath noises
- Background noise reduction to improve audio clarity
- Removal of long pauses and dead air to maintain listener engagement
- Podcast transcription with speaker detection and multiple export formats
- Podcast summarization for generating show notes and social media content
- Multitrack editing for podcasts with multiple speakers
- Timeline export for manual editing customization
- API access for automated editing at scale