Computational modelling of enculturated musical metre perception by probabilistic learning
Metre is a music-theoretic notion instructing music performers how to count beats. Music cognition research suggests that all listeners, musically trained or not, feel or perceive some correlate of metre, and that this percept forms a basic part of music experience. In fact, the experience of beat and metre appears so universal among humans, that the topic has recently started gaining attention from researchers in other fields such as biology. In search of potential evolutionary origins of musicality, these researchers became interested in which nonhuman animals share our proclivity for pulse. But since long before this widespread attention, music cognition researchers have attempted to understand beat and metre perception in empirical and modelling studies. Resulting models propose hypothetical mechanisms by which listening to a rhythm may result in the sensation of beat and metre. Little modelling work, however, has addressed metre perception’s susceptibility to perceptual learning and shaping by cultural exposure (enculturation). In this talk, I discuss some classic models of metre perception and the perspectives on cognition that they represent, before discussing some of my own work on modelling enculturation in metre perception.