P2-01: Visualization for AI-Assisted Composing
Rau, Simeon*, Heyen, Frank, Wagner, Stefan, Sedlmair, Michael
Subjects (starting with primary): MIR tasks -> similarity metrics ; Human-centered MIR ; Musical features and properties -> representations of music ; Human-centered MIR -> music interfaces and services ; Applications -> music composition
Presented In-person, in Bengaluru: 10-minute long-format presentation
We propose a visual approach for interactive, AI-assisted composition that serves as a compromise between fully automatic and fully manual composition. Instead of generating a whole piece, the AI takes on the role of an assistant that generates short melodies for the composer to choose from and adapt. In an iterative process, the composer queries the AI for continuations or alternative fill-ins, chooses a suggestion, and adds it to the piece. As listening to many suggestions would take time, we explore different ways to visualize them, to allow the composer to focus on the most interesting-looking melodies. We also present the results of a qualitative evaluation with five composers.