We Analyzed 1,533 Audio Cleanup Jobs. Two Thirds Weren't Audio Files.

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VidClean runs three tools that clean up sound: Remove Background Noise, Repair Audio, and Enhance Speech. All three are built on the same neural noise model (DeepFilterNet3), but they package it differently. Remove Background Noise strips noise and mains hum and touches nothing else. Repair Audio does the same and also normalizes loudness to broadcast level. Enhance Speech runs the full repair chain, then lets you dial how strongly the noise removal is applied with a strength slider.

Between July 20 and August 11, 2026, people ran 1,533 files through those three tools. This post is about what those jobs looked like: which tool people actually reach for, what kind of files they upload, and how long those files run.

One difference from our silence study, up front: that dataset counted seconds, so it could report hours of dead air. The audio counters store job counts and coarse buckets, not total durations, so this piece is about counts. No "hours of noise removed" number appears below because no honest one exists.

WHICH TOOL PEOPLE ACTUALLY REACH FOR

Of the 1,533 jobs in the window:

Which cleanup tool was used (1,533 jobs)

Remove Noise

818 · 53%

Repair Audio

424 · 28%

Enhance Speech

291 · 19%

Bar length is the share of all 1,533 jobs. Percentages are rounded and sum to 100.

Half the demand is the bluntest promise: make the noise go away. The two tools that do more than that, normalizing loudness or offering a blend control, split the rest.

The mix is moving, though. These three tools have lifetime counters going back to their launches in May, and the before and after look different. Before July 20, Remove Background Noise was 70% of all cleanup jobs, Repair Audio 21%, and Enhance Speech 9%. In the last three weeks Enhance Speech's share has doubled to 19%.

Part of that is a launch artifact: Enhance Speech shipped about two and a half weeks after the other two, so its lifetime share starts diluted. But correcting for days live does not close the gap. Adjusted to per-day rates, all three tools grew between the two periods, because the site's traffic grew, but they did not grow equally: Remove Background Noise runs at 3.3 times its earlier daily rate, Repair Audio at 5.5 times, and Enhance Speech at 6.5 times. The simplest tool still dominates, but the growth is concentrated in the tools that do more than delete noise.

"AUDIO CLEANUP" IS MOSTLY A VIDEO PROBLEM

Here is the number that surprised me. Of the 1,533 files uploaded for audio cleanup, 1,034 were videos. That is 67%: two out of three.

I assumed a noise removal tool would mostly see audio files: podcast WAVs, voice memos, narration tracks. Those exist, 499 of them, but they are the minority. The typical job is a video whose audio needs rescuing: a talking head clip, a screen recording, a phone video with a fan or an air conditioner humming behind it.

That reframes what these tools are for. Nobody records a video and then wants a clean MP3 back; they want the same video with the noise gone. Accordingly, all three tools hand back the same video with the cleaned audio swapped in, leaving the picture untouched wherever the format allows. The finding is that this path is not the edge case. It is the main road.

It also says something about where bad audio comes from. Dedicated audio recordings are usually made on purpose, with at least a passable microphone. Video audio is very often an afterthought: whatever the camera or phone picked up from across the room. The uploads reflect that.

THE FILES ARE CLIPS, NOT EPISODES

How long is a typical cleanup job? Short. Very short.

Length of the uploaded file (1,533 jobs)

Under 1 min

742 · 48%

1 to 5 min

574 · 37%

5 to 15 min

216 · 14%

Over 15 min

1 · under 1%

Bar length is the share of all 1,533 jobs. Percentages are rounded and sum to 99.

Nearly half of all cleanup jobs are under one minute of media. 86% are under five minutes.

One disclosure before reading too much into the right-hand tail: the free tier caps these three tools at 10 minutes per file (Pro raises it to 3 hours), so this distribution is truncated. The absence of half-hour files in the chart is partly the product's doing, not purely the users'.

The left side of the chart needs no such asterisk. Everyone in this dataset was free to upload a 10 minute file, and half of them uploaded less than one minute instead. Noise cleanup, as actually practiced, is dominated by clips: the short-form video, the single take, the one soundbite that has to be usable.

The same counters cover VidClean's other tools in the same window, which makes the shape easier to see by contrast. Files under five minutes make up 86% of audio cleanup jobs, 68% of silence removal jobs, and 55% of transcription jobs. Every one...