What is it about?

Using Bayesian statistics we demonstrate across 100 short extracts of unfamiliar music that affective responses of untrained listeners are very diverse, but show common traits: influence by acoustic intensity changes with time, and by spectral features. We assess how background tastes for music interact with these responses, showing that they have limited bearing when the music is highly unfamiliar.

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Why is it important?

In a sense, the results imply the malleability of taste: people can rapidly identify salient features of unfamiliar music, regardless of their overall liking for it. This identification may well accelerate subsequent familiarisation and diversification of taste. as our related work on recommender systems for unfamiliar music also implies.


Our hope is that installing a continuous response affect interface in a library of unfamiliar music will encourage some people to listen longer, and begin to develop some of these new tastes. To a degree, this might counter the tendency for playlists and automated recommenders to play rapidly to a shared 'lowest common deonminator' with commercial and sociopolitical bias.

Roger Dean
Western Sydney University

Read the Original

This page is a summary of: Continuous affect responses to a large diverse set of unfamiliar music: Bayesian time-series and cluster analyses., Psychomusicology Music Mind and Brain, April 2023, American Psychological Association (APA),
DOI: 10.1037/pmu0000295.
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