How to Normalize Audio Volume: Fix Quiet or Loud Files

Why Audio Files Have Different Volumes

You are listening to a playlist and every track plays at a wildly different volume. The podcast episode is barely audible, the next song blasts your eardrums, and the audiobook chapter sits somewhere in between. You keep reaching for the volume knob. This is the problem audio normalization solves.

Audio files have inconsistent volumes because they come from different sources, recorded at different levels, mixed by different engineers, and mastered to different standards. A podcast recorded in a bedroom has a different average level than a commercially mastered pop track. A quiet classical recording has a different loudness profile than a hard-limited EDM track. Without normalization, your listening experience is an exercise in constant volume adjustment.

Normalization adjusts the volume of audio files to a consistent target level, so everything in your library — or everything in your podcast feed, or every clip in your video timeline — plays at roughly the same perceived loudness. This guide covers the three main approaches to normalization, when to use each, and the exact commands and tools to apply them.

Three Types of Normalization

Not all normalization is created equal. The three approaches measure "volume" differently and produce very different results.

Peak Normalization

Peak normalization finds the loudest single sample in the audio file and adjusts the entire file's gain so that peak reaches a target level (typically 0 dBFS or -1 dBFS).

How it works: If the loudest sample is at -6 dBFS and your target is -1 dBFS, the entire file is boosted by 5 dB. Every sample gets the same gain increase.

The problem: Peak normalization tells you nothing about perceived loudness. A file with one loud transient click and otherwise quiet content will be normalized to a low average volume. A heavily compressed (dynamically, not data-compressed) file with no peaks will be normalized to a loud average volume. Two peak-normalized files can sound completely different in volume.

# Peak normalize to -1 dBFS
ffmpeg -i input.wav -af "volume=replaygain=track" output.wav

# Or more precisely:
ffmpeg -i input.wav -af "loudnorm=I=-24:TP=-1:LRA=20:print_format=summary" -f null /dev/null
# Then apply the calculated gain

When to use peak normalization:

• Before mastering (to set a consistent starting level)
• To prevent clipping in a single file
• When maximum volume without distortion is the only goal

RMS Normalization

RMS (Root Mean Square) normalization calculates the average power of the audio signal and adjusts gain so the average reaches a target level.

How it works: Instead of looking at the single loudest sample, RMS looks at the statistical average of all samples over the entire file (or a sliding window). This correlates better with perceived loudness than peak normalization, but it still does not account for the frequency-dependent sensitivity of human hearing.

# Normalize to a target RMS level
# First, measure the current RMS:
ffmpeg -i input.wav -af "volumedetect" -f null /dev/null 2>&1 | grep mean_volume

# Then adjust: if mean is -20 dB and target is -16 dB, add 4 dB
ffmpeg -i input.wav -af "volume=4dB" output.wav

When to use RMS normalization:

• Quick level matching between a few files
• Legacy workflows that predate LUFS standards
• Simple use cases where "close enough" is acceptable

Loudness Normalization (LUFS/LKFS)

Loudness normalization is the modern standard. It uses the LUFS (Loudness Units relative to Full Scale) measurement, which applies frequency weighting (K-weighting) that models how human hearing perceives loudness at different frequencies. The result correlates strongly with how loud a listener actually perceives the audio, regardless of its frequency content.

LUFS accounts for the fact that humans are more sensitive to mid-range frequencies (2-5 kHz) and less sensitive to very low or very high frequencies. A deep bass drone at -6 dBFS does not sound as loud as a voice at -6 dBFS, and LUFS captures this difference.

The EBU R128 standard specifies:

• Integrated Loudness (I): Target level in LUFS, measured over the entire program
• True Peak (TP): Maximum inter-sample peak level in dBTP
• Loudness Range (LRA): The statistical spread of loudness throughout the program, in LU

# EBU R128 loudness normalization (two-pass for accuracy)
# Pass 1: Analyze
ffmpeg -i input.wav -af loudnorm=I=-16:TP=-1.5:LRA=11:print_format=json -f null /dev/null

# Pass 2: Apply measured values
ffmpeg -i input.wav -af loudnorm=I=-16:TP=-1.5:LRA=11:measured_I=-22.3:measured_LRA=15.2:measured_TP=-3.4:measured_thresh=-33.1 -c:a pcm_s16le output.wav

Platform-Specific Loudness Targets

Different platforms have adopted different LUFS targets. Normalizing to the wrong target means the platform will either turn your audio down (if too loud) or leave it quieter than other content (if too quiet).

For YouTube-specific audio preparation, see our detailed guide on best audio format for YouTube. For podcast-specific advice, check our best audio format for podcasts.

Normalizing with FFmpeg

Single File Normalization

# Spotify/YouTube target (-14 LUFS)
ffmpeg -i input.mp3 -af loudnorm=I=-14:TP=-1:LRA=11 -c:a libmp3lame -b:a 320k output.mp3

# Apple Music / Podcast target (-16 LUFS)
ffmpeg -i input.mp3 -af loudnorm=I=-16:TP=-1:LRA=11 -c:a libmp3lame -b:a 320k output.mp3

# Broadcast target (-23 LUFS)
ffmpeg -i input.wav -af loudnorm=I=-23:TP=-1:LRA=11 -c:a pcm_s16le output.wav

Batch Normalization

#!/bin/bash
# Normalize all MP3 files in a directory to -16 LUFS
for file in /path/to/audio/*.mp3; do
  filename=$(basename "$file" .mp3)
  ffmpeg -i "$file" -af loudnorm=I=-16:TP=-1:LRA=11 \
    -c:a libmp3lame -b:a 320k \
    "/path/to/normalized/${filename}_normalized.mp3"
done

Normalizing Audio Within Video

# Normalize audio in a video file without re-encoding video
ffmpeg -i input.mp4 -c:v copy -af loudnorm=I=-14:TP=-1:LRA=11 -c:a aac -b:a 256k output.mp4

This re-encodes only the audio track while copying the video stream through unchanged. For more on working with audio in video files, see our guide on how to extract audio from video.

Using the Online Converter

If you prefer not to use command-line tools, our audio converter supports loudness normalization directly in the browser. Upload your file, select your target format and quality, and the normalization is applied automatically. For specific format needs, use our MP3 converter, WAV converter, or AAC converter.

Normalization vs. Compression vs. Limiting

These three processes are often confused but serve different purposes:

Normalization adjusts the overall gain of the entire file by a constant amount. It makes the whole file louder or quieter uniformly. The dynamic range (difference between quiet and loud parts) is preserved. A whisper and a shout will both get louder by the same amount.

Dynamic range compression reduces the difference between quiet and loud parts. It makes loud parts quieter (or quiet parts louder, or both). This changes the character of the audio — heavily compressed audio sounds "squashed" or "punchy" compared to the original. Radio stations apply aggressive compression to maintain a consistent loudness over the air.

Limiting is extreme compression that prevents the signal from exceeding a hard ceiling. A limiter at -1 dBTP allows all audio below that level to pass through unchanged but prevents anything from exceeding it. This is used as a safety measure to prevent clipping.

For most normalization tasks, you should normalize first, then limit if needed:

# Normalize then limit to prevent clipping
ffmpeg -i input.wav -af "loudnorm=I=-16:TP=-1.5:LRA=11,alimiter=limit=-1dB:level=false" -c:a pcm_s16le output.wav

ReplayGain: Non-Destructive Normalization

ReplayGain is a metadata-based normalization system. Instead of modifying the audio data, it analyzes each file and writes a gain adjustment tag into the metadata. Compatible players read this tag and adjust playback volume accordingly.

Advantages:

• Non-destructive — the original audio is never modified
• Reversible — remove the tag and the audio plays at its original volume
• Album mode — can normalize per-album (preserving intentional volume differences between tracks) or per-track

How to apply ReplayGain:

# Using loudgain (recommended)
loudgain -s e *.mp3

# Using mp3gain (older but widely used)
mp3gain -r *.mp3

# Using ffmpeg to calculate (manual application)
ffmpeg -i input.mp3 -af "replaygain" -f null /dev/null

ReplayGain is ideal for personal music libraries where you want consistent playback volume without altering your files. Most modern music players — foobar2000, Musicbee, Poweramp, VLC, AIMP — support ReplayGain tags.

Common Normalization Scenarios

Scenario 1: Podcast Episodes at Different Volumes

Multiple episodes recorded at different levels, or guest interviews where the host and guest have different volumes.

Solution: Normalize all episodes to -16 LUFS (the podcast standard). Apply per-file loudnorm:

ffmpeg -i episode.wav -af loudnorm=I=-16:TP=-1:LRA=11 -c:a libmp3lame -b:a 128k -ac 1 episode.mp3

Scenario 2: Music Playlist with Volume Jumps

A playlist where classical recordings are too quiet and pop tracks are too loud.

Solution: Apply ReplayGain to your entire library. This normalizes playback volume without modifying the files. For distribution (uploading to a platform), normalize to that platform's LUFS target.

Scenario 3: Video Dialogue Too Quiet, Effects Too Loud

Movie audio where you cannot hear dialogue but explosions shake the room.

Solution: Apply dynamic range compression before normalization:

ffmpeg -i movie.mp4 -c:v copy \
  -af "acompressor=threshold=-25dB:ratio=4:attack=5:release=100,loudnorm=I=-14:TP=-1:LRA=11" \
  -c:a aac -b:a 256k output.mp4

The compressor reduces the gap between quiet dialogue and loud effects, then loudnorm brings everything to the target level.

Scenario 4: Multiple Audio Clips for a Video Project

You have voice narration, background music, and sound effects at different levels and need them to sit together in a video.

Solution: Normalize each element separately to appropriate levels, then mix:

• Voice narration: -16 LUFS
• Background music: -24 to -30 LUFS (8-14 dB below voice)
• Sound effects: Varies by context, typically -20 to -26 LUFS

For more on working with audio in video projects, see our audio bitrate and quality guide.

Measuring Loudness

FFmpeg Analysis

# Measure integrated loudness, true peak, and loudness range
ffmpeg -i input.wav -af loudnorm=I=-16:TP=-1:LRA=11:print_format=json -f null /dev/null

This outputs:

• input_i: Integrated loudness (LUFS) — the main measurement
• input_tp: True peak (dBTP) — highest inter-sample peak
• input_lra: Loudness range (LU) — dynamic range of the program
• input_thresh: Gating threshold used for the measurement

Understanding the Numbers

• -8 LUFS: Very loud (heavily compressed modern pop/EDM)
• -14 LUFS: Spotify/YouTube target (moderate loudness)
• -16 LUFS: Apple Music/podcast target (comfortable loudness)
• -23 LUFS: European broadcast standard (quieter, wide dynamic range)
• -30 LUFS: Very quiet (classical music, ambient recordings)

The louder your audio, the less dynamic range it typically has. A track at -8 LUFS has been heavily compressed to achieve that loudness, meaning the difference between its quiet and loud moments is small. A track at -23 LUFS likely has wide dynamics — genuine quiet moments and genuine loud moments.

Mistakes to Avoid

Mistake 1: Normalizing Already-Normalized Files

Re-normalizing a file that has already been normalized is unnecessary and can introduce subtle artifacts (especially with single-pass loudnorm, which may slightly alter the tonal balance). Normalize once and track which files have been processed.

Mistake 2: Using Peak Normalization for Loudness Matching

Peak normalization does not produce consistent perceived loudness. Two files peak-normalized to 0 dBFS can have wildly different loudness. Always use LUFS-based normalization for loudness consistency.

Mistake 3: Normalizing to 0 dBFS

Normalizing peaks to 0 dBFS leaves no headroom. If you later encode to a lossy format (MP3, AAC), the transcoding process can introduce inter-sample peaks that exceed 0 dBFS, causing clipping. Always leave at least 1 dB of headroom.

Mistake 4: Ignoring the Source Quality

Normalization cannot fix fundamentally bad audio. If a recording is noisy, distorted, or heavily clipped, boosting its volume to match other files will only amplify those problems. Clean up the audio before normalizing. Our guide on how to trim audio files can help with removing problem sections.

Frequently Asked Questions

Does normalization reduce audio quality?

If done correctly, the quality impact is negligible. Loudness normalization applies a constant gain adjustment — mathematically equivalent to turning a volume knob. The only quality concern is when boosting very quiet audio, which also boosts the noise floor. If your source audio has a good signal-to-noise ratio, normalization has no audible quality impact.

Should I normalize before or after applying effects?

Normalize after all other processing (EQ, compression, reverb, etc.) is complete. Normalization should be the final step in your chain, ensuring the output meets your target loudness regardless of what the effects did to the level.

What is the difference between LUFS and LKFS?

They are the same measurement. LUFS (Loudness Units relative to Full Scale) is the European term (EBU R128 standard). LKFS (Loudness, K-weighted, relative to Full Scale) is the American term (ATSC A/85 standard). -14 LUFS and -14 LKFS are identical values.

Can I undo normalization?

If you used destructive normalization (modifying the audio file), you cannot undo it without the original file. This is why ReplayGain (non-destructive, metadata-based) is preferred for personal libraries. For files you have normalized destructively, keep backups of the originals.

Should I normalize my entire music library?

For playback consistency, yes — using ReplayGain tags (non-destructive). For distribution or uploading to platforms, normalize each file to the platform's target LUFS. But never permanently modify your master/archive files. Normalize copies, not originals. Use our FLAC converter or audio converter to create normalized copies while preserving your originals.