Infant vocal babbling strongly relies on jaw oscillations, especially at the stage of canonical babbling, which underlies the syllabic structure of world languages. In this paper, we propose, model and analyze an hypothesis to explain this predominance of the jaw in early babbling. This hypothesis states that general stochastic optimization principles, when applied to learning sensorimotor control, automatically generate ordered babbling stages with a predominant exploration of jaw movements in early stages. The reason is that those movements impact the auditory effects more than other articulators. In previous computational models, such general principles were shown to selectively freeze and free degrees of freedom in a model reproducing the proximo-distal development observed in infant arm reaching. The contribution of this paper is to show how, using the same methods, we are able to explain such patterns in vocal development. We present three experiments. The two first ones show that the recruitment order of articulators emerging from stochastic optimization depends on the target sound to be achieved but that on average the jaw is largely chosen as the first recruited articulator. The third experiment analyses in more detail how the emerging recruitment order is shaped by the dynamics of the optimization process.

中文翻译：

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通过随机优化在声音发展中的紧急下颌优势

婴儿发声强烈依赖于下巴摆动，特别是在规范的牙牙学语阶段，这是世界语言音节结构的基础。在本文中，我们提出、建模和分析了一个假设，以解释早期牙牙学语中下巴的这种优势。该假设指出，当应用于学习感觉运动控制时，一般随机优化原则会自动生成有序的咿呀学语阶段，并在早期阶段主要探索下巴运动。原因是这些运动比其他咬合架更能影响听觉效果。在以前的计算模型中，这些一般原则被证明可以在模型中选择性地冻结和释放自由度，该模型再现了在婴儿手臂伸展中观察到的近端发展。本文的贡献是展示如何，使用相同的方法，我们能够解释声音发展中的这种模式。我们提出了三个实验。前两个表明从随机优化中出现的咬合架的募集顺序取决于要实现的目标声音，但平均而言下巴主要被选为第一个募集的咬合架。第三个实验更详细地分析了优化过程的动态如何塑造新出现的招聘订单。