Perception of chord sequences modeled with prediction by partial matching, 
voice-leading distance, and spectral pitch-class similarity: A new approach for 
testing individual differences in harmony perception

Eitel, Matthew; Ruth, Nicolas; Harrison, Peter; Frieler, Klaus; Müllensiefen, Daniel

doi:10.1177/20592043241257654

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Perception of chord sequences modeled with prediction by partial matching, voice-leading distance, and spectral pitch-class similarity: A new approach for testing individual differences in harmony perception

MPS-Authors

/persons/resource/persons241822

Frieler, Klaus
Scientific Services, Max Planck Institute for Empirical Aesthetics, Max Planck Society;

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

24-ser-fri-01-perception.pdf
(Publisher version), 846KB

Supplementary Material (public)

There is no public supplementary material available

Citation

Eitel, M., Ruth, N., Harrison, P., Frieler, K., & Müllensiefen, D. (2024). Perception of chord sequences modeled with prediction by partial matching, voice-leading distance, and spectral pitch-class similarity: A new approach for testing individual differences in harmony perception. Music & Science, 7. doi:10.1177/20592043241257654.

Cite as: https://hdl.handle.net/21.11116/0000-000F-BD69-7

Abstract

The perception of harmony has been the subject of many studies in the research literature, though little is known regarding how individuals vary in their ability to discriminate between different chord sequences. The aim of the current study was to construct an individual-differences test for the processing of harmonic information. A stimulus database of 5076 harmonic sequences was constructed and several harmonic features were computed from these stimulus items. Participants were tasked with selecting which chord differed between two similar four-chord sequences, and their response data were modeled with explanatory item response models using the computational harmonic features as predictors. The final model suggests that participants’ responses can be modeled using transitional probabilities between chords, voice-leading distance, and spectral pitch-class distance cues, with participant ability correlated to three subscales from Goldsmiths Musical Sophistication Index. The item response model was used to create an adaptive test of harmonic progression discrimination ability (HPT) and validated in a second study showing substantial correlations with other tests of musical perception ability, self-reported musical abilities, and a working memory task. The HPT is a new free and open-source tool for assessing individual differences in harmonic sequence discrimination. Initial data suggest this harmonic discrimination ability relies heavily on transitional probabilities within harmonic progressions.