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[ARTICLE · art-55103] src=noiseremover.ai ↗ pub= topic=artificial-intelligence verified=true sentiment=↑ positive

Show HN: NoiseRemover.ai – Remove background noise from audio

NoiseRemover.ai launched a free browser-based tool that uses AI to remove background noise from audio recordings, supporting multiple formats and languages. The service employs open-source models like DeepFilterNet and Demucs, with automatic file deletion after processing.

read2 min views1 publishedJul 11, 2026
Show HN: NoiseRemover.ai – Remove background noise from audio
Image: source

AI audio cleanup

Clean hum, hiss, echo, wind and chatter out of any recording in seconds — then hear the before & after before you download. Free to try, no signup.

✓ No install, works in your browser ✓ Keeps your voice natural ✓ Files deleted automatically

Free demo cleans short clips. Sign in for full-length files, all formats and every tool.

29

dedicated tools

< 60s

typical clean time

100+

languages supported

8+

audio & video formats

Each tool is tuned for one job and shows a real before/after.

View all 29 Tools →

How it works #

1

Upload your audio

Drop in an MP3, WAV, M4A or even a video file — we extract the audio for you.

2

AI cleans it

Our models remove the noise while keeping your voice natural — no settings to fiddle with.

3

Hear the before & after

A/B the original against the cleaned track, then download in your chosen format.

Frequently asked questions #

Yes — you can clean short clips for free with no signup. Sign in for full-length files, every tool and all output formats.

Yes. Our denoisers apply a soft per-frequency gain rather than gating whole sections, so the noise floor drops while your voice keeps its natural tone.

MP3, WAV, M4A, FLAC, OGG and AAC audio, plus MP4 and MOV video — we extract and clean the audio track.

Your upload is used only to produce the cleaned result and is deleted automatically afterward. We never use it to train our models.

Each tool runs a dedicated pipeline on our own GPUs: your file is decoded, the audio passes through a model tuned for that one problem, and the cleaned track is returned in seconds. The AI engines under the hood are best-in-class open-source models — DeepFilterNet for denoising, Demucs for vocal and stem separation, and VoiceFixer for restoration — plus our own signal-processing filters for hum, clicks and loudness. The service itself isn't open source, but we build on and credit the open models that make it possible.

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