To become competent communicators, children need to learn that what a speaker means often goes beyond the literal meaning of what the speaker says. The acquisition of pragmatics as a field is the study of how children learn to bridge the gap between the semantic meaning of words and structures and the intended meaning of an utterance. Of interest is whether young children are capable of reasoning about others’ intentions and how this ability develops over time. For a long period, estimates of children’s pragmatic sophistication were mostly pessimistic: early work on a number of phenomena showed that very young communicators were egocentric, oblivious to other interlocutors’ intentions, and overall insensitive to subtle pragmatic aspects of interpretation. Recent years have seen major shifts in the study of children’s pragmatic development. Novel methods and more fine-grained theoretical approaches have led to a reconsideration of older findings on how children acquire pragmatics across a number of phenomena and have produced a wealth of new evidence and theories. Three areas that have generated a considerable body of developmental work on pragmatics include reference (the relation between words or phrases and entities in the world), implicature (a type of inferred meaning that arises when a speaker violates conversational rules), and metaphor (a case of figurative language). Findings from these three domains suggest that children actively use pragmatic reasoning to delimit potential referents for newly encountered words, can take into account the perspective of a communicative partner, and are sensitive to some aspects of implicated and metaphorical meaning. Nevertheless, children’s success with pragmatic communication is fragile and task-dependent.
Myrto Grigoroglou and Anna Papafragou
Katie Wagner and David Barner
Human experience of color results from a complex interplay of perceptual and linguistic systems. At the lowest level of perception, the human visual system transforms the visible light portion of the electromagnetic spectrum into a rich, continuous three-dimensional experience of color. Despite our ability to perceptually discriminate millions of different color shades, most languages categorize color into a number of discrete color categories. While the meanings of color words are constrained by perception, perception does not fully define them. Once color words are acquired, they may in turn influence our memory and processing speed for color, although it is unlikely that language influences the lowest levels of color perception. One approach to examining the relationship between perception and language in forming our experience of color is to study children as they acquire color language. Children produce color words in speech for many months before acquiring adult meanings for color words. Research in this area has focused on whether children’s difficulties stem from (a) an inability to identify color properties as a likely candidate for word meanings, or alternatively (b) inductive learning of language-specific color word boundaries. Lending plausibility to the first account, there is evidence that children more readily attend to object traits like shape, rather than color, as likely candidates for word meanings. However, recent evidence has found that children have meanings for some color words before they begin to produce them in speech, indicating that in fact, they may be able to successfully identify color as a candidate for word meaning early in the color word learning process. There is also evidence that prelinguistic infants, like adults, perceive color categorically. While these perceptual categories likely constrain the meanings that children consider, they cannot fully define color word meanings because languages vary in both the number and location of color word boundaries. Recent evidence suggests that the delay in color word acquisition primarily stems from an inductive process of refining these boundaries.
Computational psycholinguistics has a long history of investigation and modeling of morphological phenomena. Several computational models have been developed to deal with the processing and production of morphologically complex forms and with the relation between linguistic morphology and psychological word representations. Historically, most of this work has focused on modeling the production of inflected word forms, leading to the development of models based on connectionist principles and other data-driven models such as Memory-Based Language Processing (MBLP), Analogical Modeling of Language (AM), and Minimal Generalization Learning (MGL). In the context of inflectional morphology, these computational approaches have played an important role in the debate between single and dual mechanism theories of cognition. Taking a different angle, computational models based on distributional semantics have been proposed to account for several phenomena in morphological processing and composition. Finally, although several computational models of reading have been developed in psycholinguistics, none of them have satisfactorily addressed the recognition and reading aloud of morphologically complex forms.