4 papers
Getting Motif-ated: Controllable AI Compositions from Injected Motif Prompts
Chao Peter Yang, Cynthia Rudin, Yue Jiang +2
Deep learning has transformed symbolic music generation by borrowing the training paradigms of large language models, with systems such as NotaGen now producing complete, stylistic…
AutoSchA: Automatic Hierarchical Music Representations via Multi-Relational Node Isolation
Stephen Ni-Hahn, Rico Zhu, Jerry Yin +3
Hierarchical representations provide powerful and principled approaches for analyzing many musical genres. Such representations have been broadly studied in music theory, for insta…
ProGress: Structured Music Generation via Graph Diffusion and Hierarchical Music Analysis
Stephen Ni-Hahn, Chao Péter Yang, Mingchen Ma +3
Artificial Intelligence (AI) for music generation is undergoing rapid developments, with recent symbolic models leveraging sophisticated deep learning and diffusion model algorithm…
A New Dataset, Notation Software, and Representation for Computational Schenkerian Analysis
Stephen Ni-Hahn, Weihan Xu, Jerry Yin +4
Schenkerian Analysis (SchA) is a uniquely expressive method of music analysis, combining elements of melody, harmony, counterpoint, and form to describe the hierarchical structure…