MP3Conv

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Volume Booster & Normalizer

Boost a quiet file by a fixed gain, or auto-level to Spotify, YouTube and podcast loudness targets.

Mode

+6 dB doubles perceived loudness. +10 dB is "much louder". Watch for clipping above +6 dB on already-loud files.

About this volume tool

Two operations in one page: a simple gain boost and a proper broadcast-grade loudness normalizer. Use boost when a file is just too quiet — say, a voice memo recorded too far from the mic. Use normalize when you want the output to match streaming-platform loudness so it doesn't get auto-attenuated on Spotify, YouTube or podcast players.

We don't analyse or index your file.

How to boost or normalize audio

  1. 01

    Drop in audio

    MP3, WAV, FLAC, OGG, M4A and other formats are accepted.

  2. 02

    Pick boost or normalize

    Boost adds a fixed gain in dB. Normalize hits a loudness target in LUFS.

  3. 03

    Download the result

    The processed file is offered as a download in seconds.

Why use this volume tool

  • Boost gain from -10 dB up to +20 dB
  • Broadcast-grade loudness normalizer (-14, -16, -23 LUFS presets)
  • Output keeps the same format as the input
  • Free, private, no install
  • Free, no signup, no watermark
  • Great for voice memos, podcasts and music masters

Volume booster FAQ

Boost vs. normalize — which should I pick?

Boost when one specific file is too quiet and you just want it louder. Normalize when you want the file to match a platform target (Spotify is -14 LUFS, podcast standard is -16 LUFS mono / -19 stereo).

Will boosting cause clipping?

It can, if the file is already near full scale. The tool warns you when the requested gain would push the peak above 0 dBFS. Prefer normalize when you want loudness without distortion.

What is LUFS?

Loudness Units relative to Full Scale — the modern, ear-weighted way to measure loudness. Streaming platforms use it to keep tracks at consistent volume; matching their target keeps your audio from being turned down.

Is the audio re-encoded?

Yes — applying gain or loudness normalization requires re-encoding. The output uses the same format as the input at a sensible quality default.

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