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 understand this surprising phenomenon. Here, we propose start, instead, from hypotheses how might learn. To implement mechanism-driven approach, introduce a quantitative modeling framework based on large-scale simulation learning process realistic input. It allows mechanisms be systematically linked testable predictions regarding infants’ attunement language(s). Through framework, obtain evidence for an account that challenges established theories are learning.