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Durham University

Music

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Publication details for Professor Tuomas Eerola

Pearce, M. T. & Eerola, T. (2017). Music perception in historical audiences: Towards predictive models of music perception in historical audiences. Journal of Interdisciplinary Music Studies 8(1-2): 91-120.

Author(s) from Durham

Abstract

Background in Historical Musicology. In addition to making inferences about historical
performance practice, it is interesting to ask questions about the experience of historical listeners.
In particular, how might their perception vary from that of present-day listeners (and listeners at
other time points, more generally) as a function of the music to which they were exposed
throughout their lives.
Background in Music Cognition. To illustrate the approach, we focus on the cognitive process
of expectation, which has long been of interest to musicians and music psychologists, partly
because it is thought to be one of the processes supporting the induction of emotion by music.
Recent work has established models of expectation based on probabilistic learning of statistical
regularities in the music to which an individual is exposed. This raises the possibility of
developing simulations of historical listeners by training models on the music to which they
might have been exposed.
Aims. First, we aim to develop a framework for creating and testing simulated perceptual models
of historical listeners. Second, we aim to provide simple but concrete illustrations of how the
simulations can be applied in a preliminary approach. These are intended as illustrative feasibility
studies to provide a springboard for further discussion and development rather than fully fledged
experiments in their own right. Third, we aim to appeal to the expertise of historical musicologists
in identifying useful research questions and appropriate constraints for the simulations, so these
can be used to complement existing evidence on the perception of music by historical listeners.
Main contribution. Our primary contribution is to develop and illustrate a framework which we
believe can shed light on the perception of music by historical listeners and, in particular, how
listeners of different periods might have generated different predictions to music as a function of
differences in their musical experiences. The framework we develop involves several steps. First,
identifying a research question; second, selecting a corpus (or corpora) to represent the musical
experience of the listener(s) we want to simulate; third, identify the central musical features of
interest and use them to develop a representation scheme for the selected compositions; finally,
the model parameters are selected and the models are trained on the selected corpora to simulate
particular listeners. We identify and discuss the decisions that must be made at each step. Finally,
we illustrate the framework by training models on a range of corpora from different stylistic
traditions from different locations and points in history, including analyses at the level of entire
collections, individual compositions, and individual events.
Implications. The results of our illustrative analyses suggest that the trained models behave as
we hypothesised, demonstrating sensitivity to stylistic similarities which could illuminate how
listeners from different eras might have experienced musical structures. However, the approach
is in need of expertise in historical musicology to establish clear and relevant research questions
and to select appropriate parameters for the simulations. With such additional input, we believe
simulated listeners will provide important insights, alongside other evidence, into the question of
how our forebears experienced the music of their time.