Emergent Jaw Predominance in Vocal Development through Stochastic Optimization

TL;DR

This paper models how stochastic optimization principles naturally lead to early vocal babbling stages dominated by jaw movements, explaining developmental patterns observed in infant speech acquisition.

Contribution

It demonstrates that stochastic optimization can explain the emergence of jaw predominance in early vocal development, extending previous models from limb to vocal articulators.

Findings

Jaw is the first recruited articulator in most cases.

Recruitment order depends on target sounds.

Optimization dynamics influence articulator recruitment.

Abstract

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.