2013
DOI: 10.18061/emr.v8i2.3932
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Quantifying Shapes: Mathematical Techniques for Analysing Visual Representations of Sound and Music

Abstract: Research on auditory-visual correspondences has a long tradition but innovative experimental paradigms and analytic tools are sparse. In this study, we explore different ways of analysing real-time visual representations of sound and music drawn by both musically-trained and untrained individuals. To that end, participants' drawing responses captured by an electronic graphics tablet were analysed using various regression, clustering, and classification techniques. Results revealed that a Gaussian process (GP) … Show more

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Cited by 3 publications
(2 citation statements)
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“…Table 1 contains the summary statistics for the covariates, and Table 2 contains both the ungrouped and grouped emotions, where grouping of emotions is depicted in Figure 1. The majority of 2 For another innovative analysis approach using non-linear models (a Gaussian process regression model with a linear plus squared-exponential covariance function) to study crossmodal associations between music/sound and visual shapes, see Noyce et al (2013).…”
Section: Resultsmentioning
confidence: 99%
“…Table 1 contains the summary statistics for the covariates, and Table 2 contains both the ungrouped and grouped emotions, where grouping of emotions is depicted in Figure 1. The majority of 2 For another innovative analysis approach using non-linear models (a Gaussian process regression model with a linear plus squared-exponential covariance function) to study crossmodal associations between music/sound and visual shapes, see Noyce et al (2013).…”
Section: Resultsmentioning
confidence: 99%
“…Sound-tracing has also been used as a research method to understand more about our cognition of music by looking at how people move when listening to music [7,12,13,17].…”
Section: Introductionmentioning
confidence: 99%