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Distinct colours in the 'synaesthetic colour palette'

机译:“SynaeSthethic Color Palette”中的不同颜色

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In grapheme-colour synaesthesia, particular linguistic elements evoke particular colour sensations. Interestingly, when asked, non-synaesthetes can also associate colours to letters, and previous studies show that specific letter-to-colour associations have similar biases to those of synaesthetes. However, it is an open question whether the colours reported by synaesthetes and non-synaesthetes differ overall: is there a 'synaesthetic colour palette'? In this study, we visualize the overall distribution in colour space of colour concurrents in grapheme-colour synaesthetes, and colour associations in non-synaesthetic controls. We confirm the existence of a synaesthetic colour palette: colour concurrents in synaesthetes are different from colour associations in non-synaesthetes. We quantify three factors that distinguish the colour palette of synaesthetes and non-synaesthetes: synaesthetes have an increased over-representation of 'pure' (unmixed) hues, an increased presence of 'warm' (yellow, orange, brown) colours, and an increased presence of achromatic (grey, white, black) colours. Furthermore, we demonstrate that differences in the synaesthetic colour palette can be used to train a machine learning algorithm to reliably classify single subjects as synaesthetes versus non-synaesthetes without using test-retest consistency data. As far as we know, this is the first time an individual could be 'diagnosed' as a synaesthete, based only on his or her colours evoked by letters.
机译:在图形彩色的Synaesthesia中,特定语言元素唤起特定的颜色感觉。有趣的是,当被问及时,非SynaeSthetes也可以将颜色与字母联系起来,并且之前的研究表明,特定的字母到色的关联对SynaeSthetes的偏差有类似的偏见。但是,它是一个概念问题,无论是SynaeSthetes和非SynaeSthetes的颜色是否总体不同:有没有“SynaeSthetic Color Palette”?在这项研究中,我们可视化图形彩色SynaeSthetes中颜色同时的颜色空间的整体分布,以及在非SYNAESTHETIC控制中的颜色关联。我们确认存在SynaeSthethic调色板:SynaeSthetes中的颜色同时与非SynaeSthetes中的颜色关联不同。我们量化了区分SynaeSthetes和非SynaeSthetes的颜色调色板的三个因素:SynaeSthets增加了“纯粹”(纯粹'(未混合)色调的过度表示,增加了“温暖”(黄色,橙色,棕色)颜色的存在。增加了消色差(灰色,白色,黑色)颜色的存在。此外,我们证明了SynaeSthetic调色板中的差异可用于训练机器学习算法,以可靠地将单个受试者分类为SynaeSthetes,而不使用测试重新测试的一致性数据。据我们所知,这是一个人首次被“被诊断为”作为一个Synaesthete,只基于他或她的颜色被信件引起的。

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