Handytool
Audio guide5 წთ კითხვაგანახლებული 6 მაი. 2026

Neural noise removal

Cleaner voice recordings in seconds — no upload, no app.

Handytool's voice enhancer runs RNNoise, the neural network used by Discord and Jitsi, entirely inside your browser to strip fans, hum, traffic, and keyboard noise from any recording.

მთავარი მიღებული

  • 01Uses RNNoise, the same neural network behind Discord and Jitsi, to suppress noise while preserving voice.
  • 02A strength slider lets you balance aggressive cleanup against a natural-sounding result.
  • 03Processing runs in a 125 KB WebAssembly module entirely in your browser — nothing is uploaded.
  • 04Output is a mono 48 kHz WAV, ready for any audio editor or podcast host.

Why Background Noise Ruins Recordings — and How to Fix It

Fans, air conditioning, traffic, keyboard clicks, and room reverb are the most common complaints in voice recordings. A noisy mic or a bad recording environment can make an otherwise useful interview, podcast, or voice memo hard to listen to. Traditional noise gates either cut out too much or leave artifacts that sound unnatural.

Handytool's voice enhancer uses RNNoise — a recurrent neural network trained on hundreds of hours of speech data, used in production by Discord, Jitsi, and Mumble — to separate voice from noise far more cleanly than a gate alone. It runs as a 125 KB WebAssembly module directly in your browser, so your private recordings never need to touch a server.

How to Clean Up a Voice Recording Online

  1. 01

    Drop your audio file

    Drag an MP3, WAV, M4A, OGG, FLAC, or WebM file into the tool. Files up to 200 MB are accepted.

  2. 02

    Set the strength slider

    100% applies the full neural-network output for maximum noise removal. Lower values mix the cleaned signal back with the original — useful when full denoising sounds slightly robotic or when noise is already light.

  3. 03

    Click Enhance

    The denoiser processes your file locally in your browser. A progress indicator shows the status — no server round-trip is involved.

  4. 04

    Listen and download

    Preview the denoised result and download it as a 48 kHz mono WAV. If you need a smaller file, run it through the Convert audio tool to export as MP3.

Types of Noise It Handles Best

  • 01Steady fan and air conditioning hum
  • 02Traffic and outdoor ambient noise
  • 03Computer and keyboard sounds
  • 04Electrical hiss and microphone hum
  • 05Paper rustling and light room reverb

No Upload Required — Your Recordings Stay Private

The RNNoise model loads once as a 125 KB WebAssembly module and is cached in your browser. When you drop in a file, it is decoded and processed entirely on your own CPU — no data leaves your machine. This is critical for sensitive recordings: therapy sessions, legal consultations, medical notes, or unreleased content.

Processing speed is roughly 5–10 times real-time on a modern laptop, so a 10-minute interview typically enhances in under a minute. Files up to 200 MB are supported.

Voice Enhancer FAQ

How do I remove background noise from a voice recording for free?

Drop your audio file into the tool, adjust the strength slider if needed, and click Enhance. The denoised file downloads as a 48 kHz WAV — no sign-up required.

What kinds of noise does it remove?

It works best on steady noise: fans, AC hum, traffic, electrical hiss, and keyboard sounds. Very loud transients or a second voice speaking over the subject are harder cases.

What does the strength slider do?

At 100% the full neural-network output is applied. Lower values blend the cleaned signal with the original, useful when full denoising sounds too processed.

Is my audio uploaded to a server?

No. The denoising model is a WebAssembly module that runs locally on your CPU. Nothing leaves your computer.

What format does the output come in?

A mono 48 kHz 16-bit PCM WAV file. Convert it to MP3 with the Convert audio tool if you need a smaller file.

How long can the recording be?

Up to 200 MB. A 10-minute interview processes in roughly one minute on a modern laptop.

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