Source: The Verge, Mar 2017
computer engineers have created a quicker way to generate step charts for any song — using the power of neural networks.
In a paper published this week (with the quite brilliant title Dance Dance Convolution), a trio of researchers from the University of California describe training a neural network to generate new step charts. Neural networks study data to analyze patterns and then create similar-looking outputs, and in this case, there was an abundant source of data in the form of fan-written step charts.
The results are perfectly human-playable, but, as with many creative forays by artificial intelligence, professionals can still tell the difference. Speaking to The Register, step chart creator Fraxtil, who made many of the charts used to train the neural network, said, “It’s pretty easy to tell that its output is synthetic.”
“There’s a lot of creativity involved in step charting, mainly selective use of repetition and contrast, that the AI either can’t learn or can’t apply effectively,” said Fraxtil. But, they added, of all the attempts they’ve seen to auto-generate step charts, this one was by far “the most successful iteration.”