Nádia Carvalho · ICCC'20
Towards balanced tunes: A review of symbolic music representations and their hierarchical modeling
Since the heydays of music informatics, around the 1950s, the modeling and prediction of musical structures manifested as symbolic representations have been continuously pursued. The operational property of such methods is to provide the conditional distribution over an alphabet -- i.e., the entire collection of unique musical events in a composition or corpus -- given a context -- i.e., a preceding sequence. This distribution unpacks temporal morphologies that support multiple applications for predictive and assisted creative tasks, such as the generation of new musical sequences that retain a structural resemblance to a modeled source. Despite their longstanding tradition, state-of-the-art methodologies for symbolic music modeling are yet to reach the music community. Naive models such as Markov chains, which are known to neglect the fundamental hierarchical nature of musical structure, remain common practice. In this paper, we extensively review existing methodologies for symbolic music representation and modeling, as the first steps towards a study on the resulting balance across familiarity and novelty in generative music applications.
Multiple speakers · ICCC'20