Automating Musical Judgment: The Case of Mastering

A lightning talk from the Labor & Automation session of the 2017 Experts Workshop given by Jonathan Sterne (McGill University).

This talk considers the work of Landr, a Montreal company that uses machine learning to automate the process of audio mastering. Mastering is the sonic equivalent of typesetting in publishing; it puts the final polish on audio prior to its release as music, film or video game soundtracks or other forms of audio media. This talk will argue that the success of AI-based sonic judgment mastering — in stark distinction to AI-based recommendation or music mixing projects — results from the existing structure of the mastering industry. It will conclude with reflections on the implications for mastering engineers as well as users of mastering services.