Before they even speak, infants become attuned to the sounds of the language(s) they hear, processing native phonetic contrasts more easily than nonnative ones. For example, between 6 to 8 mo and 10 to 12 mo, infants learning American English get better at distinguishing English and [l], as in “rock” vs. “lock,” relative to infants learning Japanese. Influential accounts of this early phonetic learning phenomenon initially proposed that infants group sounds into native vowel- and consonant-like phonetic categories—like and [l] in English—through a statistical clustering mechanism dubbed “distributional learning.” The feasibility of this mechanism for learning phonetic categories has been challenged, however. Here, we demonstrate that a distributional learning algorithm operating on naturalistic speech can predict early phonetic learning, as observed in Japanese and American English infants, suggesting that infants might learn through distributional learning after all. We further show, however, that, contrary to the original distributional learning proposal, our model learns units too brief and too fine-grained acoustically to correspond to phonetic categories. This challenges the influential idea that what infants learn are phonetic categories. More broadly, our work introduces a mechanism-driven approach to the study of early phonetic learning, together with a quantitative modeling framework that can handle realistic input. This allows accounts of early phonetic learning to be linked to concrete, systematic predictions regarding infants’ attunement.

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Infants learn language at an incredible speed, and one of the first steps in this voyage is learning the basic sound units of their native languages. It is widely thought that caregivers facilitate this task by hyperarticulating when speaking to their infants. Using state-of-the-art speech technology, we addressed this key theoretical question: Are sound categories clearer in infant-directed speech than in adult-directed speech? A comprehensive examination of sound contrasts in a large corpus of recorded, spontaneous Japanese speech demonstrates that there is a small but significant tendency for contrasts in infant-directed speech to be less clear than those in adult-directed speech. This finding runs contrary to the idea that caregivers actively enhance phonetic categories in infant-directed speech. These results suggest that to be plausible, theories of infants' language acquisition must posit an ability to learn from noisy data.