That speakers can vary their speaking rate is evident, but how they accomplish this has hardly been studied. Consider this analogy: When walking, speed can be continuously increased, within limits, but to speed up further, humans must run. Are there multiple qualitatively distinct speech "gaits" that resemble walking and running? Or is control achieved by continuous modulation of a single gait? This study investigates these possibilities through simulations of a new connectionist computational model of the cognitive process of speech production, EPONA, that borrows from Dell, Burger, and Svec's (1997) model. The model has parameters that can be adjusted to fit the temporal characteristics of speech at different speaking rates. We trained the model on a corpus of disyllabic Dutch words produced at different speaking rates. During training, different clusters of parameter values (regimes) were identified for different speaking rates. In a 1-gait system, the regimes used to achieve fast and slow speech are qualitatively similar, but quantitatively different. In a multiple gait system, there is no linear relationship between the parameter settings associated with each gait, resulting in an abrupt shift in parameter values to move from speaking slowly to speaking fast. After training, the model achieved good fits in all three speaking rates. The parameter settings associated with each speaking rate were not linearly related, suggesting the presence of cognitive gaits. Thus, we provide the first computationally explicit account of the ability to modulate the speech production system to achieve different speaking styles. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

中文翻译：

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通过在定性上截然不同的认知“步态”之间进行切换来控制语速：来自模拟的证据。

说话者可以改变他们的说话速度是显而易见的，但是他们如何做到这一点却鲜有研究。考虑一个比喻：走路时，速度可以在限制范围内不断增加，但是要进一步加速，人类必须奔跑。是否存在多个与行走和奔跑类似的定性语音“步态”？还是通过连续调节单个步态来实现控制？这项研究通过模拟语音产生的认知过程的新连接主义者计算模型EPONA来研究这些可能性，该模型借鉴了Dell，Burger和Svec（1997）的模型。该模型的参数可以调整，以适应不同语速下语音的时间特性。我们在以不同语速产生的复音荷兰语语料库上训练了该模型。在训练过程中，针对不同的语速确定了不同的参数值（方案）簇。在1步态系统中，用于实现快慢语音的方式在质量上相似，但在数量上不同。在多步态系统中，与每个步态相关联的参数设置之间没有线性关系，从而导致参数值突然变化，从慢速说话转变为快速说话。训练后，该模型在所有三个语速上均达到了很好的匹配度。与每个语速相关的参数设置不是线性相关的，表明存在认知步态。因此，我们提供了第一个计算上显式说明的能力，可以调节语音产生系统以实现不同的讲话风格。（PsycINFO数据库记录（c）2019 APA，