  How do adults understand children's speech? Children's productions over the
course of language development often bear little resemblance to typical adult
pronunciations, yet caregivers nonetheless reliably recover meaning from them.
Here, we employ a suite of Bayesian models of spoken word recognition to
understand how adults overcome the noisiness of child language, showing that
communicative success between children and adults relies heavily on adult
inferential processes. By evaluating competing models on phonetically-annotated
corpora, we show that adults' recovered meanings are best predicted by prior
expectations fitted specifically to the child language environment, rather than
to typical adult-adult language. After quantifying the contribution of this
"child-directed listening" over developmental time, we discuss the consequences
for theories of language acquisition, as well as the implications for
commonly-used methods for assessing children's linguistic proficiency.
