Cleanvoice
It removes filler words, stutters, and mouth clicks — not noise or reverb. One honest tip from detailed testing: use Adobe Podcast for noise, then run Cleanvoice for the disfluencies, since they solve genuinely different problems.
What is Cleanvoice?
Cleanvoice, launched in 2022, does one specific job and does it thoroughly: it automatically detects and removes filler words ("um," "uh," "like," "you know"), mouth sounds (lip smacks, tongue clicks, breathing noises), stutters, and dead silence from spoken-word recordings. Upload an episode, review the proposed cuts in an editable timeline before applying them, and export a polished recording — a workflow one detailed reviewer summarizes concretely: if you're spending 2-3 hours per episode manually cutting filler words and dead air in Audacity or GarageBand, Cleanvoice can reduce that to under 15 minutes. It supports filler-word detection natively across 20-40+ languages depending on the source, with language-specific models trained on real accent variation rather than relying on generic speech recognition repurposed for the task, and an API is available for teams wanting to bake the filler-removal pass directly into an automated production pipeline.
The genuinely important, honest thing worth understanding clearly about Cleanvoice's actual scope, especially alongside Adobe Podcast and Auphonic, both covered elsewhere in this directory: Cleanvoice's core specialty is disfluencies and mouth sounds specifically, not background noise or reverb. One detailed 2026 test puts the practical guidance plainly: for noise and reverb, use a tool like Adobe Podcast, then run Cleanvoice specifically for the filler words and stutters — the two problems, and the two tools, are genuinely different, and pairing them in a pipeline (rather than expecting either alone to do everything) reflects how they're actually built to be used. It's also honest to note a real, balanced critique from hands-on testing: the automation can be overzealous, occasionally trimming natural breaths, misclassifying technical terms as filler words, or requiring manual fixes in a conventional DAW for very noisy or heavily overlapping recordings — which is exactly why reviewing proposed cuts in the editable timeline before applying them matters in practice, not just as a nice-to-have feature.
The honest scope clarification and pairing recommendation with Adobe Podcast are drawn directly from a detailed independent 2026 test (PodPosted). The "overzealous" trimming critique and language accuracy details are drawn from a separate independent review (AI Gearbase). The concrete time-savings estimate and comparison against Descript are drawn from a detailed hands-on breakdown (CreatorStackClub).
Key features
Filler word removal
Detects and cuts "um," "uh," "like," and similar hesitations automatically.
Mouth sound detection
Removes lip smacks, tongue clicks, and breathing noises from close-mic audio.
Editable timeline review
Review and adjust every proposed cut before applying it to your final file.
Long pause & silence removal
Trims dead air and awkward gaps between speech segments.
Transcription & show notes
Generates timecoded transcripts, summaries, and social-ready snippets.
API for automated pipelines
Integrates filler-removal directly into a production podcast workflow.
Pricing
Free Trial
- No signup or credit card required
- Genuinely useful — value depends heavily on how filler-heavy your show is
- A rambling conversation benefits far more than a tight script
Pay-per-minute / Subscription
- Prepay for minutes and use them as needed, no subscription required
- A recurring subscription is cheaper per hour for regular publishers
- Credit packs offer better per-minute rates at higher volumes
Higher volume tiers
- Best for production agencies and high-volume podcast networks
- Costs climb with volume, as with most usage-based tools
- Confirm current tier breakdown directly at cleanvoice.ai
Cleanvoice is a paid specialist, unlike Descript's filler-word removal bundled free into a broader editor — you're paying for stronger, more automated mouth-sound detection and API-based pipeline integration specifically. Prices reflect Cleanvoice's published pricing as of July 2026.
Available models
Integrations & platforms
Pros, cons & best for
Pros
- Genuinely thorough, specialized filler-word and mouth-sound detection
- Editable timeline lets you catch and fix over-aggressive cuts before export
- Pay-per-minute option avoids subscription waste for infrequent publishers
Cons
- Not built for noise or reverb removal — needs pairing with another tool for that
- Can occasionally trim natural breaths or misclassify technical terms as filler
- Costs climb meaningfully for high-volume or long-form producers
Best for
- Podcasters with rambling, filler-heavy conversational recordings
- Production teams wanting API-based automated cleanup pipelines
- Not the pick as a standalone tool if noise removal is your primary problem
Take a look inside
Alternatives
For noise cleanup or an all-in-one editing suite instead:
Our verdict
Cleanvoice's genuine strength is specialization — it does one narrow job, cutting filler words and mouth sounds out of rambling spoken-word recordings, more thoroughly than a general-purpose editor's bundled version of the same feature, and the tested time savings (hours down to minutes) reflect a real, practical benefit for anyone editing conversational content regularly. The honest thing worth understanding clearly before subscribing: this isn't a noise-removal tool, and pairing it with something like Adobe Podcast, already covered elsewhere in this directory, for the noise-and-reverb half of cleanup reflects how the tool is actually meant to be used rather than a limitation to work around. The editable timeline is a genuinely necessary safeguard given the tool's occasional overzealous trimming, not just a nice extra. For podcasters with genuinely filler-heavy conversational recordings needing a dedicated, thorough cleanup pass, Cleanvoice remains a strong, well-specialized choice.
FAQ
Does Cleanvoice remove background noise?
Not primarily — its core specialty is filler words, stutters, and mouth sounds. For noise and reverb removal specifically, pair it with a tool like Adobe Podcast, then run Cleanvoice for the disfluencies.
Is Cleanvoice's automation ever too aggressive?
Sometimes, yes — hands-on testing found it can occasionally trim natural breaths or misclassify technical terms as filler words, which is exactly why reviewing proposed cuts in the editable timeline before export matters in practice.
How much editing time can Cleanvoice actually save?
One detailed test estimated that manual filler-word and dead-air cutting taking 2-3 hours per episode in a tool like Audacity or GarageBand can be reduced to under 15 minutes with Cleanvoice.
How is Cleanvoice priced?
Either pay-per-minute (roughly $0.015/minute, credits that don't expire) for infrequent publishers, or a recurring subscription starting around $11/month for regular publishers, scaling up to $90-299/month for high-volume production needs.
Does Cleanvoice support languages other than English?
Yes, natively across 20-40+ languages depending on the source, using language-specific models trained on real accent variation rather than generic speech recognition repurposed for filler-word detection.
How is Cleanvoice different from Descript's filler-word removal?
Descript includes filler-word removal as one feature within a broader, more general editing suite for free; Cleanvoice is a paid specialist offering stronger, more thorough mouth-sound detection and API-based pipeline integration specifically for that one task.