01Phase 01
ITU-R BS.1770 K-Weighting Scan
Applies the BS.1770 K-weighting filters (high-shelf pre-filter and RLB high-pass) to every channel, then gates 400 ms blocks (absolute -70 LUFS, relative -10 LU) to measure integrated loudness.
ITU-R BS.1770 / EBU R128 · Peak Limiter
Normalize Audio Online Free (LUFS Meter)
Normalize dialogue, podcasts, and video audio to -14, -16, or -23 LUFS. Loudness is measured with ITU-R BS.1770 K-weighting and gating, and a -1 dBFS peak limiter catches overs. Everything runs in your browser.
Loudness Normalizer
Runs locally in your browserReady
Drop an audio or video file here
WAV, MP3, M4A, FLAC, OGG, MP4, MOV or WebM. Decoded in your browser, never uploaded.
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100% browser-local processing · No files uploaded to any server
Acoustic Engineering Guide · Architecture
How this tool works in browser memory
How this tool decodes, analyzes, and masters your dialogue locally with zero cloud latency.
02Phase 02
Target Gain Calibration
Computes the exact decibel offset required to align speech with -16 LUFS (Apple Podcasts/Spotify), -14 LUFS (YouTube/Web), or -23 LUFS (EBU R128 broadcast).
03Phase 03
True-Peak Ceiling Protection
A look-ahead peak limiter keeps every sample at or below -1.0 dBFS. True peak is estimated with 4x oversampling and shown for input and output, so you can check headroom before export.
Connected finishing workflows
Explore companion utilities for dialogue cleanup, speech pacing, and mastering.
Podcast Automixer
Balance multi-mic podcast stems before loudness mastering.
Studio Sound Enhancer
Vocal presence EQ, warmth, and high-frequency sheen.
Audio Volume Booster
Clean +18 dB gain amplification with a -1 dBFS peak limiter.
Background Noise Cleanup
80Hz rumble filter and 50/60Hz mains hum notch.
LUFS Meter
Measure first: integrated LUFS, loudness range and true peak, with pass/fail per platform.
Audio Standards & Research
Engineering guides & deep-dive workflows
Explore the acoustic principles, ITU-R loudness standards, and pacing techniques behind this tool.
LUFS9 min read
LUFS Targets for Podcasts, YouTube, Spotify and Audiobooks (2026)
A sourced table of loudness targets for Apple Podcasts, Spotify, YouTube, EBU R128 and ACX, plus integrated vs short-term, true peak and mono vs stereo.
Normalization7 min read
Audio Normalization vs Compression: What Is the Difference for Spoken Word?
Clear technical breakdown: why normalization changes overall level without affecting dynamics, while compression tames peaks and brings up quiet words.
Loudness Matching7 min read
How to Normalize Spoken-Word Audio Without Chasing a False “Perfect” Level
A sensible guide to ITU-R BS.1770 integrated loudness: understanding perceived loudness vs peak ceiling, preventing inter-sample clipping.
Frequently Asked Questions
Common Questions & Technical Clarifications
What is the difference between peak normalization and LUFS normalization?+
Peak normalization simply amplifies the loudest instantaneous sample to 0 dBFS, often leaving speech quiet or uneven. LUFS (Loudness Units Full Scale) measures perceived human loudness across the entire recording, ensuring uniform volume between different speakers and episodes.
What LUFS target should I use for podcasts vs YouTube video?+
For podcasts (Apple Podcasts, Spotify), the recommended target is -16 LUFS for stereo and -19 LUFS for mono. For YouTube and web video, the platform standard is -14 LUFS. Both targets require a -1.0 dBFS True-Peak ceiling.
Why is a True-Peak limiter at -1.0 dBFS essential for online audio?+
When streaming platforms transcode uncompressed WAV audio into lossy AAC or MP3 formats, inter-sample peaks can rise by 0.5 to 0.8 dB. Leaving about 1 dB of headroom helps prevent that distortion. This tool limits sample peaks to -1.0 dBFS and shows an estimated true peak so you can confirm the headroom.
Will normalizing audio online crush my voice dynamics?+
No. AutoSilenceCut applies one even gain change across the file and uses the look-ahead limiter only on peaks that would exceed -1.0 dBFS. Large gain increases on very dynamic audio make the limiter work harder, which can leave the result slightly under the target; the output meter shows the measured result.
Is my audio uploaded to a server for normalization?+
No. All K-weighting filters, RMS energy sums, and limiter passes execute 100% inside your local browser via Web Audio with complete data privacy.