What is it about?

Psychological expectation mechanisms have received considerable attention in music and vision. This listener study investigates the relative influence of dynamic and schematic expectations in musical and visual stimuli, and investigate the role of expertise in forming expectations by testing both musicians and non-musicians. Musicians are found to be more sensitive than non-musicians to the dynamic and schematic properties of musical stimuli, and they generally produce a wider range of expectedness ratings than non-musicians. Interestingly, musicians also interpret schematic information in the visual condition differently than non-musicians, suggesting that musical training may have influenced their expectation mechanisms more generally.

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Why is it important?

Although investigating expectation has received significant attention in music and vision, there has not been, to our knowledge, a direct comparison of the relative contribution of different types of expectation (e.g., schematic vs dynamic) within the same subjects through careful manipulation of stimuli, nor has this comparison been made across the musical and visual domains. Our results shed light on this fundamental cognitive mechanism in our expert and non-expert populations. This knowledge will come in very handy not only for better understanding music and vision expectation mechanisms, but when developing media, interfaces, technologies, and HCI systems that include musical and/or visual components.

Perspectives

I believe this paper conveys genuinely interesting results, especially in regard to how differently musicians and non-musicians perceive repeated patterns in music, and pitches that fall within vs outside of the musical key. It's also intriguing that musicians show different trends than non-musicians in the visual domain.

Kat Agres
National University of Singapore

Read the Original

This page is a summary of: Comparing Musicians and Non-musicians’ Expectations in Music and Vision, September 2022, ACM (Association for Computing Machinery),
DOI: 10.1145/3561212.3561251.
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