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5 - Ensemble Timing in String Quartets
- Edited by Michelle Phillips, Royal Northern College of Music, Manchester, Matthew Sergeant, Bath Spa University
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- Book:
- Music and Time
- Published by:
- Boydell & Brewer
- Published online:
- 07 October 2022
- Print publication:
- 10 June 2022, pp 73-96
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- Chapter
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Summary
In this chapter we examine music ensemble timing. This process, in which musicians watch and listen to sense each other and so adjust the timing of their motor actions in order to maintain good ensemble synchronisation, may be considered an example of sensorimotor synchronisation. We recount how experimental studies of the act of tapping along to a metronome – one of the simplest forms of sensorimotor synchronisation – led to the development of an internal clock model, in which self-perceived errors in synchrony between a person's taps and the metronome's beats drive phase corrections to the timing of that person's internal clock. We go on to expand this model to account for the maintenance of ensemble timing in string quartet performance. We assume each player has their own internal clock which is undergoing constant adjustment according to perceived synchrony errors between them and each of their three colleagues. Such a model is mathematically linear and describes phase correction between players. We conclude the chapter by noting that a recently developed oscillator model points the way towards a complementary, non-linear perspective on these timing adjustments between players. Both the linear and non-linear models make important contributions to our understanding of the science behind music ensemble timing, an understanding that could one day inform new approaches to rehearsal technique, and even stylistic variation, in music-making.
Introduction
Playing music in time – whether to an internally generated pulse or to an external signal such as a click track – is a complex task that relies on a number of cognitive mechanisms including perception, attention, memory, and action. In many musical styles, the desired timing of playing can be quite complex, with intended large-scale or local fluctuations in tempo or purposeful deviations from the beat. Fluctuations in the cognitive mechanisms during performance, as well as changes in neurophysiological factors affecting the muscles such as fatigue and stiffness, may result in additional, unintended variability in an individual musician's timing performance (as also discussed in Chapter 2). Despite this variability, musicians must be able to predict and adjust the temporal progression of their music-making in order to achieve their desired musical expression. When musicians play together in groups, additional challenges are put upon these mechanisms.
Driving Factors in the Colonization of Oceania: Developing Island-Level Statistical Models to Test Competing Hypotheses
- Adrian V. Bell, Thomas E. Currie, Geoffrey Irwin, Christopher Bradbury
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- Journal:
- American Antiquity / Volume 80 / Issue 2 / April 2015
- Published online by Cambridge University Press:
- 20 January 2017, pp. 397-407
- Print publication:
- April 2015
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- Article
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Migration is a key driver of human cultural and genetic evolution, with recent theoretical advances calling for work to accurately identify factors behind early colonization patterns. However, inferring prehistoric migration strategies is a controversial field of inquiry that largely relies on interpreting settlement chronologies and constructing plausible narratives around environmental factors. Model selection approaches, along with new statistical models that match the dynamic nature of colonization, offers a more rigorous framework to test competing theories. We demonstrate the utility of this approach by developing an Island-Level Model of Colonization adapted from epidemiology in a Bayesian model-selection framework. Using model selection techniques, we assess competing colonization theories of Near and Remote Oceania, showing that models of exploration angles and risk performed considerably better than models using inter-island distance, suggesting early seafarers were already adept at long-distance travel. These results are robust after artificially increasing the uncertainty around settlement times. We show how decades of thinking on colonization strategies can be brought together and assessed in one statistical framework, providing us with greater interpretive power to understand a fundamental feature of our past.