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.

翻译：本文介绍PyPhonPlan——一个基于Python的工具包，用于通过耦合动态神经场与任务动力学仿真实现语音规划的动力学建模。该工具包提供模块化组件，可用于定义规划场、感知场与记忆场，实现场间耦合与姿态输入，并利用场激活剖面求解轨迹变量路径。我们通过示例应用展示该工具包的功能：~利用耦合记忆场模拟发音/感知循环，该示例证明本框架能够使用时序原理化、神经基础化且语音信息丰富的表征对交互式语音动力学进行建模。PyPhonPlan已作为开源软件发布，内含可执行案例，以促进语音通信研究的可复现性、可扩展性与累积性计算发展。