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Bibliographic Details
Main Author: Kirkham, Sam
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2411.12720
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author Kirkham, Sam
author_facet Kirkham, Sam
contents Dynamical theories of speech use computational models of articulatory control to generate quantitative predictions and advance understanding of speech dynamics. The addition of a nonlinear restoring force to task dynamic models is a significant improvement over linear models, but nonlinearity introduces challenges with parameterization and interpretability. We illustrate these problems through numerical simulations and introduce solutions in the form of scaling laws. We apply the scaling laws to a cubic model and show how they facilitate interpretable simulations of articulatory dynamics, and can be theoretically interpreted as imposing physical and cognitive constraints on models of speech movement dynamics.
format Preprint
id arxiv_https___arxiv_org_abs_2411_12720
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Scaling laws for nonlinear dynamical models of articulatory control
Kirkham, Sam
Computation and Language
Dynamical theories of speech use computational models of articulatory control to generate quantitative predictions and advance understanding of speech dynamics. The addition of a nonlinear restoring force to task dynamic models is a significant improvement over linear models, but nonlinearity introduces challenges with parameterization and interpretability. We illustrate these problems through numerical simulations and introduce solutions in the form of scaling laws. We apply the scaling laws to a cubic model and show how they facilitate interpretable simulations of articulatory dynamics, and can be theoretically interpreted as imposing physical and cognitive constraints on models of speech movement dynamics.
title Scaling laws for nonlinear dynamical models of articulatory control
topic Computation and Language
url https://arxiv.org/abs/2411.12720