Gradual Route to Productivity: Evidence from Turkish Morphological Causatives.

Becoming productive with grammatical categories is a gradual process in children's language development. Here, we investigated this transition process by focusing on Turkish causatives. Previous research examining spontaneous and elicited production of Turkish causatives with familiar verbs attested the onset and early stages of productivity at ages 2 to 3 (Aksu-Koç & Slobin, 1985; Nakipoglu, Uzundag, & Sarigül, 2021). So far, however, we know very little about children's understanding of causatives with novel verbs. In the present study, we asked: (a) When does the generalization of causative morphology in a novel context emerge? and (b) What role does child-directed input play in this development? To answer the first question, we conducted comprehension-judgment experiments with children aged 2;6-6;11 using pseudo-verbs (Study 1 & 2). Results showed that children preferred the Turkish causative suffix -DIr over an unrelated or no suffix to denote caused events earliest at age 4;10. To answer the second question, we analyzed child-directed speech from a longitudinal corpus of Turkish language acquisition (Study 3). Results showed that when addressing children younger than age 3, caregivers used the -DIr suffix with little variation considering the overall variability of verbs they could utter. Overall, these findings suggest that productivity with morphological causatives in a novel context emerges in a later stage of acquisition. This later development might partly be accounted for by the insufficient variation of morphological causatives in the early input.

Child-directed speech is optimized for syntax-free semantic inference.

The way infants learn language is a highly complex adaptive behavior. This behavior chiefly relies on the ability to extract information from the speech they hear and combine it with information from the external environment. Most theories assume that this ability critically hinges on the recognition of at least some syntactic structure. Here, we show that child-directed speech allows for semantic inference without relying on explicit structural information. We simulate the process of semantic inference with machine learning applied to large text collections of two different types of speech, child-directed speech versus adult-directed speech. Taking the core meaning of causality as a test case, we find that in child-directed speech causal meaning can be successfully inferred from simple co-occurrences of neighboring words. By contrast, semantic inference in adult-directed speech fundamentally requires additional access to syntactic structure. These results suggest that child-directed speech is ideally shaped for a learner who has not yet mastered syntactic structure.