Linking Sonic Aesthetics with Mathematical Theories

Milne, Andrew J.

doi:10.1093/oxfordhb/9780190226992.013.6

Cited by 3 publications

(2 citation statements)

References 32 publications

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“…Periodic patterns, like those described by trigonometry and more straightforward cyclic repetitions, are prominent in many natural systems and found in many aspects of music and acoustics (Milne 2018). In music, these are found in the undulating pulsation of a low frequency oscillator for vibrato or tremolo effects, they can outline the rise and fall of melodic contours and can represent the dynamic pulsation of metric rhythms.…”

Section: Periodicitymentioning

confidence: 99%

Live Coding Patterns and a Toolkit for Pure Data

Brown

2023

Org. Sound

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Creative activities often involve specific processes and techniques that reflect the unique nature of the activity. For live coders, these processes and techniques can be expressed as algorithms and functions in live coding languages. In many fields, these idiomatic processes are referred to as design patterns. Design patterns are important to understand because they can structure thought and direct users towards particular outcomes. This article examines the design patterns in live coding practices and languages, specifically focusing on the Live Coding Toolkit for Pure Data. Pure Data is a visual programming language, but few live coders have traditionally used it. This article explains how the Live Coding Toolkit allows Pure Data to effectively express the patterns of practice required for successful music live coding performance.

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Section: Periodicitymentioning

confidence: 99%

Live Coding Patterns and a Toolkit for Pure Data

Brown

2023

Org. Sound

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“…Well-formed rhythms are of interest because they are highly syncopated, common in non-Western traditions (e.g., the Bembe and aksak rhythms shown above), have interesting compositional possibilities (Milne, 2018;Milne & Dean, 2016), and are defined for periodicities of any length (such as the familiar 3-, 4-, 6-, 8-, 9-, and 12-pulse periods, and the less familiar 5-, 7-, 10-, 11-, and 13-pulse periods).…”

Section: 2mentioning

confidence: 99%

The effects of rhythmic structure on tapping accuracy

Milne¹,

Dean²,

Bulger³

2021

Preprint

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By modelling tapping behaviour – rhythm-level tapping accuracy and pulse-level tap probabilities, velocities, and timing errors – to 91 unfamiliar and complex rhythms, we uncover novel cognitive mechanisms that play a role in temporal prediction. This was achieved with multilevel Bayesian regression using a large number of mostly new predictors, each derived from the structure of the rhythm and each indicative of one or more underlying cognitive mechanisms. This is the first synchronized tapping study to use such a wide variety of unfamiliar rhythms and the results show that, for these tricky rhythms, participants’ taps are disrupted by unfamiliar period lengths and are guided by rather crude encodings of each rhythm: the density of rhythmic cues, their circular mean and variance, and recognizing common small patterns and the approximate positions of groups of cues. These lossy encodings are often counterproductive for discriminating between cued and uncued pulses and are quite different to mechanisms – such as metricization and emphasizing group boundaries – thought to guide tapping behaviours in learned and familiar rhythms.

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The effects of rhythmic structure on tapping accuracy

Milne,

Dean,

Bulger

2023

Atten Percept Psychophys

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Prior investigations of simple rhythms in familiar time signatures have shown the importance of several mechanisms; notably, those related to metricization and grouping. But there has been limited study of complex rhythms, including those in unfamiliar time signatures, such as are found outside mainstream Western music. Here, we investigate how the structures of 91 rhythms with nonisochronous onsets (mostly complex, several in unfamiliar time signatures) influence the accuracy, velocity, and timing of taps made by participants attempting to synchronize with these onsets. The onsets were piano-tone cues sounded at a well-formed subset of isochronous cymbal pulses; the latter occurring every 234 ms. We modelled tapping at both the rhythm level and the pulse level; the latter provides insight into how rhythmic structure makes some cues easier to tap and why incorrect (uncued) taps may occur. In our models, we use a wide variety of quantifications of rhythmic features, several of which are novel and many of which are indicative of underlying mechanisms, strategies, or heuristics. The results show that, for these tricky rhythms, taps are disrupted by unfamiliar period lengths and are guided by crude encodings of each rhythm: the density of rhythmic cues, their circular mean and variance, and recognizing common small patterns and the approximate positions of groups of cues. These lossy encodings are often counterproductive for discriminating between cued and uncued pulses and are quite different to mechanisms—such as metricization and emphasizing group boundaries—thought to guide tapping behaviours in learned and familiar rhythms.

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Linking Sonic Aesthetics with Mathematical Theories

Cited by 3 publications

References 32 publications

Live Coding Patterns and a Toolkit for Pure Data

Live Coding Patterns and a Toolkit for Pure Data

The effects of rhythmic structure on tapping accuracy

The effects of rhythmic structure on tapping accuracy

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