A Dynamical Model of Pitch Memory Provides an Improved Basis for Implied Harmony Estimation

Frontiers in Psychology
Ji Chul Kim

Abstract

Tonal melody can imply vertical harmony through a sequence of tones. Current methods for automatic chord estimation commonly use chroma-based features extracted from audio signals. However, the implied harmony of unaccompanied melodies can be difficult to estimate on the basis of chroma content in the presence of frequent nonchord tones. Here we present a novel approach to automatic chord estimation based on the human perception of pitch sequences. We use cohesion and inhibition between pitches in auditory short-term memory to differentiate chord tones and nonchord tones in tonal melodies. We model short-term pitch memory as a gradient frequency neural network, which is a biologically realistic model of auditory neural processing. The model is a dynamical system consisting of a network of tonotopically tuned nonlinear oscillators driven by audio signals. The oscillators interact with each other through nonlinear resonance and lateral inhibition, and the pattern of oscillatory traces emerging from the interactions is taken as a measure of pitch salience. We test the model with a collection of unaccompanied tonal melodies to evaluate it as a feature extractor for chord estimation. We show that chord tones are selectively enhanced...Continue Reading

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Citations

Apr 3, 2019·Physical Review. E·Ji Chul Kim, Edward W Large
Jan 6, 2021·Biological cybernetics·Ji Chul Kim, Edward W Large

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Methods Mentioned

BETA
feature extraction

Software Mentioned

GrFNN Toolbox

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