In the Mix: AI Support for Live DJ Track Selection

Disc jockeys (DJs) play a central role in shaping dance-floor experiences. To achieve their overall goals for their set, DJs solve a difficult optimization problem each time they choose a song. They consider local song compatibility, involving genre, tempo, harmonic alignment, and groove, with the desired energy and direction of the set in response to the crowd. We present a framework, OptiMix, with an interactive visual tool that allows the DJ to formulate and solve this optimization problem during a live set. Our tool allows the DJ to weigh various factors when adjusting custom distance metrics between songs. We introduce a novel dimension reduction algorithm, SmoothMAP, to visualize the songs according to the DJ's distance metric. SmoothMAP is a general algorithm and can be used broadly for problems where we expect smooth changes in dimension reduction plots when smoothly adjusting the weights within the distance metric. OptiMix allows DJs to think more broadly about their goals for the set and better optimize song choices in accordance with those goals.