PyPhonPlan: Simulating phonetic planning with dynamic neural fields and task dynamics

TL;DR

PyPhonPlan is an open-source Python toolkit that models phonetic planning using dynamic neural fields and task dynamics, enabling simulation of interactive speech processes with neural and phonetic detail.

Contribution

It introduces a modular, neural-grounded framework for simulating phonetic planning and speech dynamics, with executable examples for reproducibility and extension.

Findings

Demonstrates modeling of production/perception loops in speech

Shows capability to simulate interactive speech dynamics

Provides a flexible, neural-based simulation toolkit

Abstract

We introduce PyPhonPlan, a Python toolkit for implementing dynamical models of phonetic planning using coupled dynamic neural fields and task dynamic simulations. The toolkit provides modular components for defining planning, perception and memory fields, as well as between-field coupling, gestural inputs, and using field activation profiles to solve tract variable trajectories. We illustrate the toolkit's capabilities through an example application:~simulating production/perception loops with a coupled memory field, which demonstrates the framework's ability to model interactive speech dynamics using representations that are temporally-principled, neurally-grounded, and phonetically-rich. PyPhonPlan is released as open-source software and contains executable examples to promote reproducibility, extensibility, and cumulative computational development for speech communication research.