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.

翻译：言语动态理论通过发音控制的计算模型生成定量预测并深化对言语动态的理解。在任务动态模型中加入非线性恢复力相较于线性模型是显著改进，但非线性特性带来了参数化和可解释性方面的挑战。我们通过数值模拟阐明这些问题，并提出以标度律形式呈现的解决方案。我们将标度律应用于立方模型，展示其如何促进发音动态的可解释模拟，并可从理论上阐释为对言语运动动态模型施加物理与认知约束。