Modelling of Musical Perception using Spectral Knowledge Representation.
| Autor: | Homer ST; Computational Creativity Lab, Artificial Intelligence Research Group, Vrije Universiteit Brussel, Belgium., Harley N; Computational Creativity Lab, Artificial Intelligence Research Group, Vrije Universiteit Brussel, Belgium., Wiggins GA; Computational Creativity Lab, Artificial Intelligence Research Group, Vrije Universiteit Brussel, Belgium.; Cognitive Science Research Group, School of Electronic Engineering and Computer Science, Queen Mary University of London, UK. |
|---|---|
| Jazyk: | angličtina |
| Zdroj: | Journal of cognition [J Cogn] 2024 Apr 08; Vol. 7 (1), pp. 32. Date of Electronic Publication: 2024 Apr 08 (Print Publication: 2024). |
| DOI: | 10.5334/joc.356 |
| Abstrakt: | We present a novel approach to representing perceptual and cognitive knowledge, spectral knowledge representation , that is focused on the oscillatory behaviour of the brain. The model is presented in the context of a larger hypothetical cognitive architecture. The model uses literal representations of waves to describe the dynamics of neural assemblies as they process perceived input. We show how the model can be applied to representations of sound, and usefully model music perception, specifically harmonic distance. We demonstrate that the model naturally captures both pitch and chord/key distance as empirically measured by Krumhansl and Kessler, thereby providing an underlying mechanism from which their toroidal model might arise. We evaluate our model with respect to those of Milne and others. Competing Interests: The authors have no competing interests to declare. (Copyright: © 2024 The Author(s).) |
| Databáze: | MEDLINE |
| Externí odkaz: |
|