In the rapidly evolving landscape of digital media, audio quality acts as the gatekeeper of engagement. Whether you are a veteran podcaster, a video creator, or a corporate communications manager, the clarity of your audio directly influences audience retention. Listeners today have little patience for background hums, distractingly loud breaths, or uneven volume levels. This demand for studio-quality sound has given rise to a new generation of Audio Processing tools powered by artificial intelligence.
The purpose of this comparison is to dissect two of the market's leading contenders: Cleanvoice AI and Auphonic. While both tools aim to automate the post-production process, they approach the challenge from distinct angles. One focuses heavily on linguistic cleaning—removing "ums," "ahs," and stuttering—while the other acts as a comprehensive audio engineer in a box, focusing on loudness standards and signal processing.
Understanding the nuances between these platforms is crucial. Choosing the right tool can save hours of manual editing time and significantly improve the production value of your content. This analysis will guide you through their features, integration capabilities, and pricing models to help you decide which solution fits your workflow.
Cleanvoice AI is a specialized tool designed with a singular mission: to make spoken audio sound natural and professional by removing the artifacts of human speech. Its key selling point is its proprietary "Filler Word Removal" algorithm. Unlike traditional noise gates that only cut silence, Cleanvoice understands context. It detects filler words (like "um," "ah," "you know"), heavy clicking mouth sounds, and stuttering. Its mission is to streamline the editing process for creators who want a "drag-and-drop" solution that cleans up the narrative flow without stripping the life out of the voice.
Auphonic has established itself as a staple in the Podcast Editing community. It positions itself not just as a cleaner, but as an automated post-production service. Auphonic’s background is rooted in signal processing and broadcasting standards. Its core positioning revolves around technical compliance—ensuring your audio hits the correct LUFS (Loudness Units relative to Full Scale) targets for platforms like Spotify, Apple Podcasts, and Netflix. While it does offer noise reduction, its strength lies in leveling, normalization, and handling complex multi-track projects.
To understand where these tools overlap and diverge, we must look at their technical capabilities in detail.
| Feature | Cleanvoice AI | Auphonic |
|---|---|---|
| Primary Focus | Linguistic cleanup (fillers, stutters) | Signal processing (loudness, leveling) |
| Noise Reduction | AI-based background noise removal | Adaptive noise gate and hum reduction |
| Silence Removal | Context-aware shortening | Truncate silence with threshold controls |
| Leveling | Basic volume normalization | Adaptive Leveler (Broadcast standards) |
| Multitrack Support | Limited (focuses on single mix or stems) | Advanced (Crossgate, Ducking, Crosstalk) |
Cleanvoice AI excels at identifying non-speech artifacts. Its Noise Reduction is aggressive against mouth sounds and lip smacking, which are notoriously difficult to remove manually. It creates a "dry" studio sound. Auphonic, conversely, uses intelligent algorithms to learn the noise print of a file. It is exceptional at removing static background hums (like air conditioning) but is less focused on the wet mouth noises that Cleanvoice targets.
This is Auphonic’s home turf. Its Adaptive Leveler balances speech and music segments seamlessly, amplifying quiet speakers while compressing loud outbursts. It also applies a global loudness normalization (e.g., -16 LUFS for stereo) automatically. Cleanvoice AI ensures volume is consistent, but it lacks the granular control over EQ profiles and broadcast compliance that Auphonic offers.
Both platforms utilize AI to distinguish between speakers. Cleanvoice uses this primarily to ensure it doesn't accidentally cut a breath that serves as a cue for the next speaker. Auphonic uses speaker identification for its multitrack algorithms to prevent "crosstalk" (bleed from one microphone to another). Both services can generate transcriptions, though they are often used as secondary features to the audio processing.
For high-volume production houses and developers, the ability to automate workflows via API is a deciding factor.
Cleanvoice AI offers a modern, RESTful API that allows developers to integrate its cleaning algorithms into their own apps. It is particularly popular among startup platforms building "AI editor" features. For the non-technical user, Cleanvoice is primarily web-based, though they have experimented with plugins for DAWs (Digital Audio Workstations) like Adobe Audition or DaVinci Resolve in beta stages.
Auphonic boasts one of the most mature integration ecosystems in the industry. It supports:
For developers requiring extensive documentation and proven stability in high-load environments, Auphonic retains the edge.
Cleanvoice AI offers a minimalist, modern interface. The user journey is designed for simplicity: upload a file, select which "cleaning" modules to activate (e.g., "Remove Stutters," "Remove Dead Air"), and process. The results are presented with a visual timeline showing exactly what was cut, allowing users to manually approve or reject specific edits. This transparency is a massive UX win.
Auphonic’s interface is more utilitarian and arguably steeper in learning curve. It presents a form-based input method where users select presets, algorithms, and output formats. While less visually "slick" than Cleanvoice, it offers distinct accessibility advantages for power users who want to save specific "Presets" for different shows.
Cleanvoice Workflow:
Auphonic Workflow:
Both tools process audio faster than real-time. Auphonic is superior for batch processing large archives, allowing users to queue 50 episodes at once. Cleanvoice is fast but is generally treated as a per-episode tool for creators refining content before the final mix.
Support quality often dictates the long-term viability of a tool in a professional workflow.
For Podcast Editing, the choice depends on the raw material. If the guest has a nervous tick and says "um" every three seconds, Cleanvoice AI is the savior. It fixes the performance. If the recording is clean but the volume is inconsistent because one person was on Zoom and the other in a studio, Auphonic is the solution. It fixes the technical fidelity.
Video creators (YouTubers/TikTokers) favor Cleanvoice AI. The ability to tighten up a script by automatically removing dead air creates the "jump cut" style of pacing that is popular on social media, without the manual razor tool work.
Auphonic is widely used in lecture capture systems and corporate archives. Its ability to take a folder of Zoom recordings and standardize them to a listenable volume without human intervention makes it ideal for enterprise Content Creation workflows.
Ideal Users for Cleanvoice AI:
Ideal Users for Auphonic:
Cleanvoice typically operates on a subscription model based on hours of processing.
Auphonic uses a flexible credit system.
Cost Comparison: For low-volume users, Auphonic is cheaper (often free). For heavy users requiring granular editing of speech patterns, Cleanvoice commands a premium but delivers a specialized result Auphonic cannot replicate.
In our testing for this review, we analyzed processing speed and audio fidelity.
While this article compares Cleanvoice and Auphonic, the market is crowded.
The battle between Cleanvoice AI and Auphonic is not truly a zero-sum game; they solve different problems within the audio spectrum.
Cleanvoice AI is an Editor. It fixes the content of the audio—the stuttering, the hesitations, and the mouth noises. It is best for content creators who want to make their speakers sound eloquent and confident.
Auphonic is a Mixing Engineer. It fixes the signal—the volume, the hum, and the file metadata. It is best for creators who want their final file to sound compliant, professional, and consistent across all devices.
Final Recommendation:
If your raw audio suffers from bad microphone technique or nervous speakers, start with Cleanvoice AI. If your recording is decent but you need to mix an intro, outro, and ensure it hits -16 LUFS for Spotify, finish with Auphonic. For the ultimate professional workflow, many top-tier creators actually use both: Cleanvoice to tidy up the speech, followed by Auphonic for the final master.
Q: Can I use Cleanvoice and Auphonic together?
A: Yes. The best workflow is to run your raw audio through Cleanvoice first to remove fillers and mouth sounds, then upload that exported file to Auphonic for leveling, loudness normalization, and tagging.
Q: Do these tools work with video files?
A: Auphonic supports video input and can export video files with the enhanced audio track replacing the original. Cleanvoice generally accepts video files for processing but focuses on the audio track; check their latest update for video export capabilities.
Q: Is my data safe with these AI tools?
A: Both companies state that they delete data after a processing period. Auphonic is based in Europe and is GDPR compliant. Cleanvoice also adheres to strict privacy standards regarding user data.
Q: Which tool is better for beginners?
A: Auphonic’s free tier (2 hours/month) makes it the best starting point for beginners with zero budget. However, Cleanvoice’s interface is more intuitive for someone who doesn't understand audio terminology like "LUFS" or "Noise Gate."
Q: Does Cleanvoice remove background wind noise?
A: It has background noise reduction capabilities, but it is optimized for mouth sounds and fillers. For heavy environmental noise (wind, traffic), Auphonic or specialized tools like Adobe Podcast Enhance might perform better.