Empirical Musicology: Aims, Methods, Prospects

By Eric Clarke; Nicholas Cook | Go to book overview

CHAPTER 6
Computational and Comparative Musicology

Nicholas Cook


Introduction

The middle of the twentieth century saw a strong reaction against the comparative methods that played so large a part in the disciplines of the humanities and social sciences in the first half of the century, and musicology was no exception. The term “comparative musicology” was supplanted by “ethnomusicology,” reflecting a new belief that cultural practices could only be understood in relation to the particular societies that gave rise to them: it was simply misleading to compare practices across different societies, the ethnomusicologists believed, and so the comparative musicologist was replaced by specialists in particular musical cultures. A similar reaction took place in theory and analysis: earlier style-analytical approaches (largely modeled on turn-of-the-century art history) gave way to a new emphasis on the particular structural patterns of individual musical works. Perversely, this meant that the possibility of computational approaches to the study of music arose just as the idea of comparing large bodies of musical data—the kind of work to which computers are ideally suited—became intellectually unfashionable. As a result, computational methods have up to now played a more or less marginal role in the development of the discipline.

In this chapter I suggest that recent developments in computational musicology present a significant opportunity for disciplinary renewal: in the terms introduced in chapter 1, there is potential for musicology to be pursued as a more datarich discipline than has generally been the case up to now, and this in turn entails a re-evaluation of the comparative method. Central to any computational approach, however, are the means by which data are represented for analysis, and so I begin with some examples of “objective” data representations before introducing the issue of comparison. (The examples I discuss are graphic, but the same points could have been made in terms of numerical representations.) This is followed by an extended case study of an important current software package for musicological research, the Humdrum Toolkit, and the chapter concludes with a brief consideration of the prospects for computational methods in musicology.

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