Photo: Future |
Considered the single biggest advancement in software development over the past few years, this technology is possible thanks to revolutionary advancements in computing power and data storage, and is now an integral part of day-to-day life, like how Siri or Alexa intelligently store data to predict future actions. Ever wondered why Facebook’s ‘People You May Know’ and those pesky suggested ads on social media are always so accurate? Spooky, huh? That’s before we even mention face recognition software, email spam filtering, image classification, fraud detection…
Yep, machine learning algorithms are everywhere, and the field of music is no exception. For us everyday music listeners here in 2019, streaming services’ algorithms drive those lists of suggestions that help you hunt down new songs and artists you’d never normally discover. Last year, Google’s Magenta research division developed the open-source NSynth Super, a synthesiser powered by their NSynth algorithm designed to create entirely new sounds by learning the acoustic qualities of existing ones...
How can musicians harness this technology while retaining creativity?
“There are a couple of different research camps. One from the world of musicology, focused on algorithmic musical composition. In this space you have Amper Music, who have a product that can create generative music examples for your content, like your YouTube video or ad. Others focus on applications like auto-accompaniment. So some groups are trying to automate creativity, and others are trying to enhance it.
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Source: MusicRadar