Key clarity is blue, relaxed, and maluma : machine learning used to discover cross-modal connections between sensory items and the music they spontaneously evoke

![CDATA[Semantic differential is often used to investigate the relationship between music and other sensory modalities such as colors, tastes, vision, and odors. This work proposes an exploratory approach including open-ended responses and subsequent machine learning to study cross-modal associations, based on a recently developed sensory scale that does not use any explicit verbal description. Twenty-five participants were asked to report a piece of music they considered close to the feel/look/experience of a given sensory stimulus. Results show that the associations reported by the participants can be explained, at least in part, by a set of features related to some timbric and tonal aspects of music.]]