Sound Properties Associated With Equiluminant Colours

in Multisensory Research
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There is a widespread tendency to associate certain properties of sound with those of colour (e.g., higher pitches with lighter colours). Yet it is an open question how sound influences chroma or hue when properly controlling for lightness. To examine this, we asked participants to adjust physically equiluminant colours until they ‘went best’ with certain sounds. For pure tones, complex sine waves and vocal timbres, increases in frequency were associated with increases in chroma. Increasing the loudness of pure tones also increased chroma. Hue associations varied depending on the type of stimuli. In stimuli that involved only limited bands of frequencies (pure tones, vocal timbres), frequency correlated with hue, such that low frequencies gave blue hues and progressed to yellow hues at 800 Hz. Increasing the loudness of a pure tone was also associated with a shift from blue to yellow. However, for complex sounds that share the same bandwidth of frequencies (100–3200 Hz) but that vary in terms of which frequencies have the most power, all stimuli were associated with yellow hues. This suggests that the presence of high frequencies (above 800 Hz) consistently yields yellow hues. Overall we conclude that while pitch–chroma associations appear to flexibly re-apply themselves across a variety of contexts, frequencies above 800 Hz appear to produce yellow hues irrespective of context. These findings reveal new sound–colour correspondences previously obscured through not controlling for lightness. Findings are discussed in relation to understanding the underlying rules of cross-modal correspondences, synaesthesia, and optimising the sensory substitution of visual information through sound.

Sound Properties Associated With Equiluminant Colours

in Multisensory Research



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    Chroma adjustments for pure tones, complex sine waves and vocal timbres. Panel a illustrates the relationship between the frequency of pure tones for set 1 (grey diamonds) and set 2 (red squares) and chroma average adjustments. Panel b illustrates the same relationship, but with z-scored frequency to account for range effects within each stimulus set. Panel c illustrates results for pure tones that vary in loudness. Panel d illustrates the results for vocal frequency bands that vary in their average frequency. Panels e and f illustrate complex sine wave and vocal timbre sounds that vary in their ‘centre of gravity’. Key: p<0.05, ∗∗p<0.01, ∗∗∗p<0.001.

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    Chroma adjustments for all stimulus sets in which the average frequency varied. Panel a illustrates the relationship between chroma and frequency (z-scored) across all stimulus sets in which the average frequency varied. Panel b illustrates the average chroma adjustments across all stimulus sets in which the average frequency varied. Key: ∗∗∗p<0.001.

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    Change of hue with frequency, loudness, and ‘centre of gravity’. Statistics in the upper left corners report the correlation across all stimuli varying in frequency (pure tones set 1, set 2, vocal frequency bands) based on Fisher’s z-transform across individuals (panel a), different levels of pure tone loudness (panel b), and different levels of ‘centre of gravity’ (panel c). Key: ∗∗p<0.01, ∗∗∗p<0.001. Note that hue adjustments change linearly as a function of frequencies for pure tones and vocal frequency bands (panel a), and as a function of loudness (panel b); but stay almost constant for sounds that vary in their centre of gravity (panel c). A more detailed breakdown of hue for individual stimuli and sets can be found in Supplementary Figs S1 and S2.

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