There’s much chatter in AI circles about how machines can now compose things like production music for use in the background of videos and in audio commercials. This didn’t just happen overnight. Medium explains the long evolution of algorithmic music.
Algorithmic music composition has developed a lot in the last few years, but the idea has a long history. In some sense, the first automatic music came from nature: Chinese windchimes, ancient Greek wind-powered Aeolian harps, or the Japanese water instrument suikinkutsu. But in the 1700s automatic music became “algorithmic”: Musikalisches Würfelspiel, a game that generates short piano compositions from fragments, with choices made by dice.
Markov chains, formalized in the early 1900s to model probabilistic systems, can also be used to generate new musical compositions. They take the motivations behind the dice game a step further, in two ways. First, Markov chains can be built from existing material rather than needing fragments explicitly composed as interchangeable components. Second, instead of assuming fragments have equal probabilities, Markov chains encode the variation in probabilities with respect to context.
This is really fascinating. Read on.