Early phonetic learning without phonetic categories: Insights from large-scale simulations on realistic input

Significance Infants become attuned to the sounds of their native language(s) before they even speak. Hypotheses about what is being learned by infants have traditionally driven researchers’ attempts to understand this surprising phenomenon. Here, we propose to start, instead, from hypotheses about how infants might learn. To implement this mechanism-driven approach, we introduce a quantitative modeling framework based on large-scale simulation of the learning process on realistic input. It allows learning mechanisms to be systematically linked to testable predictions regarding infants’ attunement to their native language(s). Through this framework, we obtain evidence for an account of infants’ attunement that challenges established theories about what infants are learning.