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Approaches in Intelligent Music Production

School of Electronic Engineering and Computer Science, Queen Mary University of London, London E1 4NS, UK
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Arts 2019, 8(4), 125; https://doi.org/10.3390/arts8040125
Received: 18 July 2019 / Revised: 9 September 2019 / Accepted: 10 September 2019 / Published: 25 September 2019
(This article belongs to the Special Issue Music and the Machine: Contemporary Music Production)
Music production technology has made few advancements over the past few decades. State-of-the-art approaches are based on traditional studio paradigms with new developments primarily focusing on digital modelling of analog equipment. Intelligent music production (IMP) is the approach of introducing some level of artificial intelligence into the space of music production, which has the ability to change the field considerably. There are a multitude of methods that intelligent systems can employ to analyse, interact with, and modify audio. Some systems interact and collaborate with human mix engineers, while others are purely black box autonomous systems, which are uninterpretable and challenging to work with. This article outlines a number of key decisions that need to be considered while producing an intelligent music production system, and identifies some of the assumptions and constraints of each of the various approaches. One of the key aspects to consider in any IMP system is how an individual will interact with the system, and to what extent they can consistently use any IMP tools. The other key aspects are how the target or goal of the system is created and defined, and the manner in which the system directly interacts with audio. The potential for IMP systems to produce new and interesting approaches for analysing and manipulating audio, both for the intended application and creative misappropriation, is considerable. View Full-Text
Keywords: intelligent music production; automatic mixing; adaptive audio effects; audio processing; artificial intelligence; machine learning intelligent music production; automatic mixing; adaptive audio effects; audio processing; artificial intelligence; machine learning
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Moffat, D.; Sandler, M.B. Approaches in Intelligent Music Production. Arts 2019, 8, 125.

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