Mastering Music Using Izotope Ozone 9
Mastering EDM music and all the other genres can be a hard process. Mastering techniques are a different cam to mixing music.
Its that final step in mixing and mastering that can be the final push to making a good track sound great.
What we’re going to do together in this course is take your from kind of knowing what each tool does in Izotope Ozone 9. To being a mastering master of Ozone 9.
By the end of this course you will be able to understand fully what each tool does in Izotope’s Ozone 9. And when and why to use each tool.
You will be able to take your own music to a level where its ready for commercial release, And even rent out your new skill set for client work as well.
In Mastering Music with Ozone 9 we cover
What is mastering
All of the tools inside Ozone 9
How to use tools and techniques to fix certain issues
How to master a track step by step
Why true peak is important to note
How bit depth will affect your end result
The best way to export for a streaming release
If you’re new to using Ozone or been here before, There’s something here for you as we cover new ground with the latest features available to Ozone with version 9, Applying the latest and most modern mastering techniques.
Introduction to Ozone 9
What is Limiting
The Ozone 9 Modern Modules
The Ozone 9 Vintage Modules
Ultra Modern Modules
In this tutorial i'm going to show you that with Ozone 9, you can match to any reference track to an extreme degree with an EQ that uses over 8,000 separate bands to get the most precise snapshot possible. New region parameters now give you more control over the end result by letting you choose what parts of the audio to match. Capture a reference from a track in your session, or a reference file loaded into Ozone 9, and save your favorite results as presets for easy access. Take an imprint of your reference track and save time finding the right EQ balance with this mastering engineer’s secret weapon.
Add the Match EQ Curves to the "Global Presets" folder of Ozone 9
Mastering Tracks with Ozone 9
The loudness of your music depends on how Loudness Normalization relates to your master.
Here are a few reasons why your music may sound different than others:
A track that is very dynamic but mastered to -14 dB LUFS will have its peak levels preserved when played on Spotify. If you compare that to a loudly mastered track, at - 6 dB LUFS for example, its peaks get lowered to - 8 dB LUFS. The two tracks will play back at the same perceived loudness level, but the loud or “peak” parts of the more dynamic track will be much louder.
If you’re playing your album in shuffle, or in between tracks from other albums (such as in a playlist), track normalization is used. For more info about this, see My album is deliberately mastered to have some tracks softer than others. Will this get lost on Spotify?
You have inaudible high-frequency content in your mix. Loudness algorithms (both ReplayGain and ITU 1770) do not have a lowpass cut-off filter, meaning any high-frequency content will add up to the energy measured by the algorithms and your track will be measured as louder by the algorithms than is actually perceived.
You have a really loud master (true peaks well above -2 dB) which makes the encoding add some distortion, adding to the overall energy of the track. That’s the energy as perceived by the algorithm, which might be inaudible to you but adds to the loudness from the algorithm’s perspective.
You’re not listening to a linear playback system. The ReplayGain algorithm (just like the ITU 1770 algorithm) can’t guess what audio playback system you’re using, so can’t compensate for non-linearity in your system. Meaning, tracks that have more energy in the frequencies your system lifts up will sound much louder on your system.
As we’re still using the ReplayGain algorithm, you may encounter differences between that and the ITU 1770 algorithm, meaning what you expect from measuring your track with a loudness meter (we recommend ITU 1770) is not exactly what we measure for your track using ReplayGain.
What is Loudness Normalization and why is it used?
Audio files are delivered to Spotify from distributors all over the world and are often mixed/mastered at different volume levels. We want to ensure the best listening experience for users, so we apply Loudness Normalization to create a balance.
It also levels the playing field between soft and loud masters. Louder tracks have often been cited as sounding better to listeners, so Loudness Normalization removes any unfair advantage.
Note: The web player and Spotify apps integrated into third-party devices (such as speakers and TVs) don’t currently use Loudness Normalization.
How does Spotify adjust loudness?
When we receive your audio file, we transcode it to delivery formats Ogg/Vorbis and AAC. At the same time, we calculate the loudness level and store that information as metadata in the transcoded formats of your track.
Playback levels are not adjusted when transcoding tracks. Tracks are delivered to the app with their original volume levels, and positive/negative gain compensation is only applied to a track while it’s playing. This gives users the option to adjust the Loudness Normalization if they want to.
Negative gain is applied to louder masters so the loudness level is at ca - 14 dB LUFS. This process only decreases the volume in comparison to the master; no additional distortion occurs.
Positive gain is applied to softer masters so that the loudness level is at ca - 14 dB LUFS. A limiter is also applied, set to engage at -1 dB (sample values), with a 5 ms attack time and a 100 ms decay time. This will prevent any distortion or clipping from soft but dynamic tracks.
The gain is constant throughout the whole track, and calculated to match our desired output loudness level.