COSMOS: Computational Shaping and Modeling of Musical Structures

This position paper makes the case for an innovative, multi-disciplinary methodological approach to advance knowledge on the nature and work of music performance, driven by a novel experiential perspective, that also benefits analysis of electrocardiographic sequences. Music performance is considered by many to be one of the most breathtaking feats of human intelligence. It is well accepted that music performance is a creative act, but the nature of its work remains elusive. Taking the view of performance as an act of creative problem solving, ideas in citizen science and data science, optimization, and computational thinking provide means through which to deconstruct the process of music performance in scalable ways. The method tackles music expression's lack of notation-based data by leveraging listeners' perception and experience of the structures elicited by the performer, with implications for data collection and processing. The tools offer ways to parse a musical sequence into coherent structures, to design a performance, and to explore the space of possible interpretations of the musical sequence. These ideas and tools can be applied to other music-like sequences such as electrocardiographic recordings of arrhythmias (abnormal heart rhythms). Leveraging musical thinking and computational approaches to performance analysis, variations in expressions of cardiac arrhythmias can be more finely characterized, with implications for tailoring therapies and stratifying heart rhythm disorders.

Automated summary

This position paper proposes an innovative, multi-disciplinary approach to advancing knowledge on music performance, leveraging listeners' perception and experience to analyze music sequences. It also introduces the use of computational thinking to explore variations in expressions of cardiac arrhythmias.