How can you standardize audio volume levels using normalization?

Imagine you're trying to bring together a group of singers with wildly different volumes. Normalization is like a vocal coach for audio files, gently adjusting their levels to create a harmonious balance. It's a technique that modifies the amplitude (loudness) of an audio signal without affecting its quality or dynamics. This means you can even up the playing field for different songs, podcasts, or videos without making them sound squashed or unnatural.

Put simply, software samples a file finding the maximum level within, then it increases overall volume to come to a standard “norm.” This can be good and bad, and batch software has never been as effective as the human ear. Things to consider include such questions— do I want the drums to stand out, if so will the desired mix cause issues when normalizing the volume level against multiple tracks in the same collection. Different types of music may demand different norms, and therefore normalization should be approached with a game plan. My advice, do not assume there is an easy fix across the board. Trust your instincts against the selected final product.

Think of peak normalization as setting a ceiling for loudness. It scans your audio file and identifies the highest peak (think of it as the loudest singer), then adjusts the entire track's volume so that peak reaches a specific level, usually 0 dBFS (decibels relative to full scale). This ensures all your audio files play back at the maximum possible volume without clipping or distortion, just like ensuring everyone stays within their vocal range while still belting out those high notes!

Loudness normalization takes a more nuanced approach, considering not just the highest peak but the overall perceived loudness of the audio. It analyzes the content over time, taking into account factors like the distribution of audio energy and psychoacoustic principles of how humans perceive sound. This helps ensure a consistent listening experience across different audio types, like transitioning smoothly from a soft ballad to a dynamic rock song without needing constant volume adjustments.

True peak normalization is the meticulous accountant of the audio world. It goes beyond the standard 0 dBFS limit and accounts for inter-sample peaks, which are tiny spikes that can't be directly captured by digital systems but can potentially cause clipping during playback on certain devices. Think of it as double-checking all the numbers to ensure there are no hidden discrepancies that might disrupt the audio.

In the halcyon days of when people used to listen to the radio and there was only the BBC and very few independent stations, I was a presenter on the only dedicated Rock Music radio programme on the BBC - Extravaganza. Even though we weren’t staff we still had to learn how to drive the desk. The BBC rules were : speech peaks at 8, music peaks at 6. Reason being that, dynamically, recordings were all over the place in those days. When the independent FM stations came on air, they started putting everything through compression and limiters to save the DJs constantly chasing the faders. Nowadays all broadcasts go through these dynamic limitations and, consequently, it’s no longer such a priority with originating creativity.

You'd be surprised at how many "masters" are low volume. I always use a normalizer to get them to radio levels. DJs don't like inconsistent levels on their program material, and why should I make them work?

Choosing the right normalization method depends on your specific needs and context. Peak normalization is simple and effective for basic volume leveling, while loudness normalization provides a more consistent listening experience across diverse content. True peak normalization is essential for mastering professional audio or preparing for broadcast, while understanding the target platform's loudness standards is crucial for optimal playback.

Batch Processing: Normalize multiple files simultaneously for efficiency. Undo Functionality: Revert changes if the normalization doesn't produce desired results. Experiment with Settings: Explore different target levels and methods to find the best fit for your audio. Normalize for Specific Platforms: Consider loudness standards for different platforms (e.g., Spotify, YouTube) if applicable. Apply Compression and EQ: Use these tools before normalization to control dynamic range and tonal balance. Consider Multi-Band Loudness Normalization: This method analyzes and adjusts loudness across different frequency bands for more refined control.

Lossy vs. lossless audio: Normalization affects different formats differently. Lossy formats like MP3 may suffer slight quality degradation with repeated normalization. Batch processing: Some software allows batch normalization, saving you time when dealing with multiple audio files. Non-destructive editing: Choose software that allows non-destructive editing, so you can always revert to the original audio if needed. By understanding the different normalization methods and factors to consider, you can achieve consistent and high-quality audio levels for your projects, podcasts, or personal listening experience.