The concepts of beat and meter are well-established terms in music production and perception. Most authors agree that beat induction, the cognitive ability that allows one to infer a regular beat (or pulse) from a musical excerpt, is universal in and unique to humans, enabling us to entrain to music, and coordinate our movements with others. Formal models (e.g., Longuet-Higgins & Lee, 1984) specify metric salience, a value assigned to each sequential position of a rhythmic sound pattern regarding to its position within that measure, by recursively breaking down a musical pattern (with an initially specified length) into sub-patterns of equal length.
The number of recursive subdivisions needed to arrive at a given point (event) in a rhythmic pattern governs the salience of that point (i.e. salience-vector): the more subdivisions needed, the lower the perceived salience of that point. In general, it holds that the higher the salience of an event compared to other events within the same metrical unit, the more listeners expect it to occur. Longuet-Higgins was the first to try and formalize the notion of syncopation from a cognitive perspective. (BTW he was also the first to coin the term �cognitive science� for a then emerging field of research; Longuet-Higgins, 1987.)
The project aims to make Longuet-Higgins' formalization more precise, generalize its definition based on a formalization of the notion of meter, incorporate refinements of the resulting salience vector based on recent empirical data (Ladinig & Honing, in preparation), and elaborate all this in an algorithm that will describe the full, empirically validated model of syncopation.
