# Scaling laws for nonlinear dynamical models of articulatory control

arXiv: https://arxiv.org/abs/2411.12720 · HTML: https://mlsanity.com/paper/2411.12720/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 17 references that are in the map.
- First posted on arXiv 19 Nov 2024.

## Builds on (most cited first, 1 of 1)

- [Neural inhibition during speech planning contributes to contrastive hyperarticulation](https://mlsanity.com/paper/2209.12278/) (2022)

## Built on by (most cited first, 3 of 3)

- [Dynamical model parameters from ultrasound tongue kinematics](https://mlsanity.com/paper/2510.18629/) (2025)
- [Phonetic accommodation and inhibition in a dynamic neural field model](https://mlsanity.com/paper/2502.01210/) (2025)
- [Discovering dynamical laws for speech gestures](https://mlsanity.com/paper/2504.04849/) (2025)

## Abstract (arXiv)

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.