Janssen Rick, Moisik Scott R, Dediu Dan
Language and Genetics Department, Max Planck Institute for Psycholinguistics, Nijmegen, The Netherlands.
Linguistics and Multilingual Studies, Nanyang Technological University, Singapore, Singapore.
PLoS One. 2018 Feb 15;13(2):e0191557. doi: 10.1371/journal.pone.0191557. eCollection 2018.
People vary at most levels, from the molecular to the cognitive, and the shape of the hard palate (the bony roof of the mouth) is no exception. The patterns of variation in the hard palate are important for the forensic sciences and (palaeo)anthropology, and might also play a role in speech production, both in pathological cases and normal variation. Here we describe a method based on Bézier curves, whose main aim is to generate possible shapes of the hard palate in humans for use in computer simulations of speech production and language evolution. Moreover, our method can also capture existing patterns of variation using few and easy-to-interpret parameters, and fits actual data obtained from MRI traces very well with as little as two or three free parameters. When compared to the widely-used Principal Component Analysis (PCA), our method fits actual data slightly worse for the same number of degrees of freedom. However, it is much better at generating new shapes without requiring a calibration sample, its parameters have clearer interpretations, and their ranges are grounded in geometrical considerations.
从分子层面到认知层面，人类在大多数水平上都存在差异，硬腭（口腔的骨性顶部）的形状也不例外。硬腭的变异模式对法医学和（古）人类学很重要，在病理情况和正常变异中，其在言语产生方面可能也发挥着作用。在此，我们描述一种基于贝塞尔曲线的方法，其主要目的是生成人类硬腭的可能形状，以用于言语产生和语言进化的计算机模拟。此外，我们的方法还可以使用少量且易于解释的参数来捕捉现有的变异模式，并且仅用两三个自由参数就能很好地拟合从MRI扫描轨迹获得的实际数据。与广泛使用的主成分分析（PCA）相比，在相同自由度数量的情况下，我们的方法对实际数据的拟合效果稍差。然而，在无需校准样本的情况下生成新形状方面，我们的方法要好得多，其参数具有更清晰的解释，并且其范围基于几何考虑。
