The field of language acquisition examines the interaction between children and their environment in the acquisition of a first language.
Language acquisitionists at Maryland are working toward explicit models of the innate contribution of the learner and how this contribution makes it possible for learners to construct a specific grammar of the language to which they are exposed. Because learning mechanisms rely in part on real-time sentence understanding mechanisms, acquisitionists at Maryland are working to specify how psycholinguistic processing contributes to language learning.
In addition, because the acquisition of linguistic meaning depends on understanding the cognitive systems that interface with language, a growing research area in the department examines the interplay between cognitive and linguistic development. Formally explicit computational models are becoming a widely applied research tool in language acquisition at Maryland. Such models make explicit the relative contribution of the learner and the environment and make it possible to compare alternative hypotheses in novel ways.
Finally, our research is conducted in a broadly cross-linguistic context, helping us identify how the language learning capacity is robust to the wide range of variation found in the world's languages. Languages currently under investigation include: English, Ewe, Kannada, Korean, Mandarin, Norwegian, Tagalog, Tsez and Japanese. Recent areas of interest include binding constraints, quantification, argument structure, A-bar movement, noun-class learning, phrase structure, attitude verbs and implicature.
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Social inference may guide early lexical learning
Assessment of knowledgeability and group membership influences infant word learning.
We incorporate social reasoning about groups of informants into a model of word learning, and show that the model accounts for infant looking behavior in tasks of both word learning and recognition. Simulation 1 models an experiment where 16-month-old infants saw familiar objects labeled either correctly or incorrectly, by either adults or audio talkers. Simulation 2 reinterprets puzzling data from the Switch task, an audiovisual habituation procedure wherein infants are tested on familiarized associations between novel objects and labels. Eight-month-olds outperform 14-month-olds on the Switch task when required to distinguish labels that are minimal pairs (e.g., “buk” and “puk”), but 14-month-olds' performance is improved by habituation stimuli featuring multiple talkers. Our modeling results support the hypothesis that beliefs about knowledgeability and group membership guide infant looking behavior in both tasks. These results show that social and linguistic development interact in non-trivial ways, and that social categorization findings in developmental psychology could have substantial implications for understanding linguistic development in realistic settings where talkers vary according to observable features correlated with social groupings, including linguistic, ethnic, and gendered groups.
Japanese children's knowledge of the locality of "zibun" and "kare"
Initial errors in the acquisition of the Japanese local- or long-distance anaphor "zibun."
Although the Japanese reflexive zibun can be bound both locally and across clause boundaries, the third-person pronoun kare cannot take a local antecedent. These are properties that children need to learn about their language, but we show that the direct evidence of the binding possibilities of zibun is sparse and the evidence of kare is absent in speech to children, leading us to ask about children’s knowledge. We show that children, unlike adults, incorrectly reject the long-distance antecedent for zibun, and while being able to access this antecedent for a non-local pronoun kare, they consistently reject the local antecedent for this pronoun. These results suggest that children’s lack of matrix readings for zibun is not due to their understanding of discourse context but the properties of their language understanding.
There is a simplicity bias when generalising from ambiguous data
How do phonological learners choose among generalizations of differing complexity?
How exactly do learners generalize in the face of ambiguous data? While there has been a substantial amount of research studying the biases that learners employ, there has been very little work on what sorts of biases are employed in the face of data that is ambiguous between phonological generalizations with different degrees of complexity. In this article, we present the results from three artificial language learning experiments that suggest that, at least for phonotactic sequence patterns, learners are able to keep track of multiple generalizations related to the same segmental co-occurrences; however, the generalizations they learn are only the simplest ones consistent with the data.