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Tonal Cognition
Author(s) -
KRUMHANSL CAROL L.,
TOIVIAINEN PETRI
Publication year - 2001
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1111/j.1749-6632.2001.tb05726.x
Subject(s) - tonality , chord (peer to peer) , key (lock) , tone (literature) , computer science , task (project management) , representation (politics) , speech recognition , musical , art , distributed computing , computer security , literature , management , politics , political science , law , economics , visual arts
A bstract : This article presents a self‐organizing map (SOM) neural network model of tonality based on experimentally quantified tonal hierarchies. A toroidal representation of key distances is recovered in which keys are located near their neighbors on the circle of fifths, and both parallel and relative major/minor key pairs are proximal. The map is used to represent dynamic changes in the sense of key as cues to key become more or less clear and modulations occur. Two models, one using tone distributions and the other using tone transitions, are proposed for key‐finding. The tone transition model takes both pitch and temporal distance between tones into account. Both models produce results highly comparable to those of musically trained listeners, who performed a probe tone task for ten nine‐chord sequences. A distributed mapping of tonality is used to visualize activation patterns that change over time. The location and spread of this activation pattern is similar for experimental results and the key‐finding model.