Readers 读者
Control strategy of physiological articulatory model for speech production
面向言语产生的发音生理模型控制方法
Xiyu Wu 吴西愉; Jianwu Dang 党建武
Abstract 摘要
In speech production the articulatory apparatus includes the organs that execute efferent motor commands from the central nervous system. In order to simulate the behavior of the articulatory apparatus, computational modeling is a commonly-used method. We have constructed a full 3D physiological articulatory model that includes the tongue, jaw, hyoid bone and vocal-tract wall based on the continuum finite element method. This model comprises articulatory muscles with realistic properties and geometrical arrangements. The muscle activation patterns are used to control the movements of the model. In order to use the model to investigate the speech motor control mechanism, generate speech sounds, predict the effect of surgical operation, etc., we have to realize an automatic control strategy. The task of the control strategy is given a particular target, how to generate muscle activation patterns that can control the model to achieve the target. There are two main control strategies for the physiological articulatory model: feedforward control and feedback control. Feedforward control is a kind of mapping used to directly find muscle activation patterns according to the desired target, and feedback control is used to adjust muscle activation patterns to reduce the distance between the desired target and the realized position. In speech production, feedforward mapping is used to rapidly generate muscle activation patterns to control the articulators to produce fluent speech. Feedback control plays the role of learning and maintaining the feedforward mapping. When the degree of accuracy using feedforward mapping cannot satisfy the requirement, feedback control can be used to realize fine motor control. In this paper, we describe how to use feedback control as a learning loop to construct feedforward mapping. The constructed feedforward mapping was assessed through an open-set test, and reasonable articulatory positions were obtained by comparison with the desired targets. Furthermore, the ability of feedback control to improve control accuracy was proved by a large quantity of simulations.
SUBJECT KEYWORDS: Speech production Physiological Articulatory Model Muscle activation pattern Speech motor control
在言语产生的过程中，发音器官是执行来自中枢神经系统的运动指令的终端组织。电脑建模的方法常常被应用于模拟发音器官的行为。为此，我们使用连续体有限元的方法建立了一个三维的发音器官的生理模型，该模型包含舌、下颌、舌骨以及声道壁等发音器官。该模型还包括了根据其生理解剖属性建立的用于控制发音器官运动的肌肉模型。为了将该生理模型应用于探索发音器官的运动控制机制，产生自然流畅的语音，对发音器官的手术后功能进行预测等，我们需要对模型建立一个自动的控制机制。控制机制的任务在于给定一个发音目标，如何自动的产生肌肉激活模式去控制模型到达目标。对于发音器官的生理模型而言，有两种主要的控制方式：前馈控制和回馈控制。前馈控制是一种从发音控制目标到肌肉激活模式的映射，用于根据发音目标产生肌肉激活模式；而回馈控制主要用于调整肌肉激活模式来减少模型实现的位置到目标之间的距离，最终控制模型到达目标。在言语产生的过程中，前馈控制用于快速的产生肌肉激活模式控制发音器官产生流畅的语音。回馈控制主要用于学习前馈控制的映射，并且维持前馈控制可行性。当前馈控制的精度不能满足需求时，回馈控制可以用于提高控制精度以实现精确控制。在本文中，我们将重点介绍如何使用回馈控制作为学习回路，建立前馈控制的映射。对已建立的前馈映射的开集测试表明该映射可以用于控制模型在误差允许范围内达到目标。而且，大量的模型模拟表明回馈控制可用于改善前馈控制的控制精度。
Keywords 关键词
Speech production 言语产生 Physiological Articulatory Model 发音生理模型 Muscle activation pattern 肌肉激活模式 Speech motor control 发音器官运动控制