Senior Lecturer Marcus Pearce is currently guest researcher at MIB and will give a talk.

22.08.2017 | Hella Kastbjerg

Title:
Steve Reich's Clapping Music: Balancing Ecological Validity and Experimental Control in the Study of Music Production and Perception
 

Abstract:

Ecological validity is considered an important factor in experimental design and yet the vast majority of studies use artificially constructed stimuli that bear little relation to those encountered in real life. This problem is especially pronounced in the psychological and neuroscientific study of cultural domains like music. The difficulty with using genuine pieces of music as stimuli is that multiple musical parameters will usually vary simultaneously in rather complex and not entirely systematic ways resulting in a loss of experimental control (though, of course, this is one of the reasons we enjoy listening to music).

In much of my research, I use computational modelling as a way of characterising the physical and perceptual properties of complex real-world musical examples which allows one to retain ecological validity while mitigating to some extent the loss of experimental control.

Here, I will present a different approach in two studies, of music production and perception respectively, that use minimalist music to simultaneously achieve both high ecological validity and experimental control. Both studies use as stimulus materials Clapping Music, composed by the American minimalist composer Steve Reich. The first uses an app developed for IoS that presents users with a game-based approach to learning to perform Clapping Music which provides us with data from over 100,000 users worldwide that are analysed to examine which aspects of rhythmic structure influence performance timing. The second study examines rhythmic similarity perception between the different component parts of Clapping Music, showing that similarity perception is asymmetrical and is influenced by musical training and expressive performance. A general-purpose compression-based model of similarity perception is introduced that accounts well for the behavioural data.    

Read more about Marcus here:

http://webprojects.eecs.qmul.ac.uk/marcusp/index.php?page=0