PP-2004-14: Computational modeling of music cognition: A case study on model selection

PP-2004-14: Honing, Henkjan (2004) Computational modeling of music cognition: A case study on model selection. [Report]

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Abstract

While the most common way of evaluating a computational model is to see whether it shows a good fit with the empirical data, recent literature on theory testing and model selection criticizes the assumption that this is actually strong evidence for the validity of a model. This paper presents a case study from music cognition (modeling the ritardandi in music performance) and compares two families of computational models (kinematic and perceptual) using three different model selection criteria: goodness-of-fit, model's simplicity, and the degree of surprise in the predictions. In the light of what counts as strong evidence for a model's validity - namely that it makes precise, non-smooth, and relatively surprising predictions - the perception-based model is preferred over the kinematic model.

Item Type: Report
Report Nr: PP-2004-14
Series Name: Prepublication (PP) Series
Year: 2004
Uncontrolled Keywords: model selection, theory testing, music cognition, computational modeling
Subjects: Cognition
Depositing User: Henkjan Honing
Date Deposited: 12 Oct 2016 14:36
Last Modified: 12 Oct 2016 14:36
URI: https://eprints.illc.uva.nl/id/eprint/125

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