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AI cleanup for podcasts: filler words, noise, mouth sounds
Cleanvoice does one thing well: it strips filler words, noise, and mouth sounds out of spoken audio and saves hours of manual editing. Multilingual support and a review-before-cut editor are real strengths. It is not a full editing suite, and automated cuts still deserve a human review pass, but as a targeted cleanup step in a podcast workflow it is efficient and fairly priced.
Cleanvoice is a focused AI tool that automatically removes filler words, stutters, mouth sounds, background noise, and dead air from podcasts and voice recordings across 40+ languages. It offers a review editor so creators can confirm cuts before exporting. Priced by processing hours with a free allowance, it is a time-saving cleanup step rather than a full editing suite.
Cleanvoice is a focused AI tool for cleaning up spoken-word audio. Upload a podcast episode, interview, or voiceover and it automatically detects and removes verbal filler such as "um," "uh," and "you know," plus stutters, long silences, mouth clicks, lip smacks, and background noise. The goal is to cut the tedious, repetitive part of audio editing so creators spend less time scrubbing waveforms and more time publishing. The service works across 40+ languages for filler detection and can process the audio track of video podcasts while keeping it in sync with the video. It provides an editor where you can review and confirm what the AI proposes to cut, which helps avoid the over-aggressive edits that pure automation sometimes makes. It positions itself as a time-saver that complements, rather than fully replaces, a human editor. Cleanvoice prices primarily by audio processing hours, with a small free allowance, monthly plans keyed to hours per month, and a pay-per-minute option for irregular use. It is a bootstrapped, independent company, which shows in its narrow, well-executed focus: it does the podcast-cleanup job well without trying to be a full DAW or hosting platform.
Cleanvoice is a focused AI cleanup tool that removes filler words, mouth sounds, noise, and dead air from podcasts and voice recordings in 40+ languages. It offers a review-before-cut editor and is priced by processing hours with a small free tier. It is a time-saving step in an editing workflow, not a full DAW, and automated cuts still merit human review.
Cleanvoice is an independent, bootstrapped company founded in 2021, focused specifically on AI-assisted cleanup of spoken-word audio. Its narrow scope reflects a small-team, product-focused approach.
The company competes in the fast-growing podcast-tooling space by doing a single job (automated audio cleanup) well and integrating into creators' existing editing and hosting workflows.
Cleanvoice detects and removes filler words, stutters, mouth sounds, background noise, and silences, then presents the proposed edits in an editor for review. It supports 40+ languages and can process the audio of video podcasts in sync.
An API allows the cleanup to be integrated into automated pipelines, and exports fit into standard podcast editing and hosting workflows.
Podcasters, interviewers, and voice-content creators, including multilingual producers, who want to automate repetitive audio-cleanup tasks.
Podcast hosts, editors, and voice-content creators cleaning up recordings.
Individual creators and small podcast teams on self-serve plans.
Podcasting communities, audio-editing educators, and creator tool reviewers.
A regular podcaster or small production team that records conversational audio and wants to cut hours of manual filler and noise editing per episode.
No funding publicly disclosed. Public databases describe Cleanvoice as a bootstrapped, unfunded company; verify with primary sources.
It automatically detects and removes filler words, stutters, mouth sounds like lip smacks and clicks, background noise, and long silences from spoken-word recordings.
Cleanvoice handles filler-word detection in 40+ languages, making it useful for non-English podcasts and multilingual creators.
It processes the audio track of video podcasts and keeps it in sync with the video, but it is an audio-cleanup tool rather than a video editor.
Automated tools can be aggressive, which is why Cleanvoice provides an editor to review and confirm proposed cuts before exporting. A human review pass is still recommended.
Primarily by audio processing hours, with a small free allowance, monthly hour-based plans, and a pay-per-minute option for occasional use.
Side-by-side pages for pricing, features, and best-fit use cases.
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