Polaris Studios | Mastered for iTunes
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“Mastered for iTunes”

Whether you are an independent artist, a recording label or a TV or film producer, you provide the central and most important element to the equation:  the music itself.

At Polaris, it is our job to faithfully and accurately deliver your songs, albums or any other kind of audio material to audiences around the world exactly as you intend them to be heard.  In recent years, Apple has developed a group of audio mastering tools, designed to facilitate the achievement of the best possible results, ones that live up to the highest standards of the music available on the main music provider for consumers around the world these days:  The iTunes Store.  With over 900 million iOS devices capable of playing your music, it’s essential for professional mastering studios to count on specialized tools to craft, optimize and codify our finished works to be perfectly played back on these devices.

When iTunes launched in 2001, the central topic was to standardize audio contents under a new format design, called Advanced Audio Coding (AAC) instead of the more popular MP3 format, simply because AAC clearly provides superior audio quality compared to other codecs at similar bit rates.  By working with Dolby and Fraunhofer, there have since been further improvements to AAC to get it to the level of excellence experienced on iTunes nowadays.  A selection of Mastering studios can offer finished works based in AAC encoding guidelines to achieve dynamic range and general overall sound that are even superior to those stated in the Red Book audio standard (link acá al Red Book), yielding a final product that’s virtually indistinguishable from the original recording.

What’s the difference between the “Mastered for iTunes” format and other high-end finished mastering works?

To understand this point, it’s necessary to count on a little knowledge of the basic challenges when encoding audio to high resolution formats.  You can get a general perspective here:
Sample Rate

An inherent challenge of working with high resolution audio has been that both the sample rate and the bit depth must be reduced to match the specifications used in mainstream distribution, such as CD or AAC.  This can be done either with software (“in the box encoding ”) or by running the mix through an additional high-quality analog stage and resampling.  There are pros and cons with each technique, as both of these can add noise and/or distortion.


Downsampling, as the word implies, is the process of using Sample Rate Conversion (SRC) to lower the sample rate (for example, from 96kHz to 44.1kHz). This process commonly creates aliasing, an undesired effect.

Dithering (or dithering down)

Is a technique used when reducing a file’s bit depth (for example, from 24-bit to 16-bit).  It’s an attempt to reduce the distortion inherent to this process.  However, dithering is a tradeoff, as the distortion is reduced at the cost of added noise.  Other option to reduce distortion is by simply “truncating” the audio file; this is, removing information bits from the digital audio content.  This is again a tradeoff because of the potential quantization distortion that it implies.

The solutions

The solutions provided by Apple’s current encoding methodology imply in a 2-step process:

The first step in the encoding path is to use state-of-the-art, mastering-quality Sample Rate Conversion (SRC) to resample the master file to a sample rate of 44.1kHz.  Because this SRC outputs a 32-bit floating-point file, it can preserve values that might otherwise fall outside of the permitted amplitude range.  This critical intermediary step prevents any aliasing or clipping that could otherwise occur in SRC, and it is this 32-bit floating file that’s used as the input to the final encoder.


The second step compresses the use of encoders that use every bit of resolution available, preserving all the dynamic range of a 24-bit source file and eliminating the need for dithering. This has a double advantage, as it not only does obviate the need of adding dither noise but also lets the encoders work more efficiently as they don’t need to waste resources encoding unwanted and unnecessary noise.