Publications

Abstract

This entry takes an interdisciplinary approach to linguistic pragmatics. It discusses how the meaning of utterances can only be understood in relation to overall cultural, social, and interpersonal contexts, as well as to culture-specific conventions and the speech events in which they are embedded. The entry discusses core issues of pragmatics such as speech act theory, conversational implicature, deixis, gesture, interaction strategies, ritual communication, phatic communion, linguistic relativity, ethnography of speaking, ethnomethodology, and conversation analysis. It takes a transdisciplinary view of the field, showing that linguistic pragmatics has its predecessors in other disciplines such as philosophy, psychology, ethology, ethnology, and sociology.

Abstract

No idea is older in the history of linguistics than the thought that there is, somehow hidden underneath the surface of sentences, a form or a structure which provides a semantic analysis and lays bare their logical structure. In Plato’s Cratylus the theory was proposed, deriving from Heraclitus’ theory of explanatory underlying structure in physical nature, that words contain within themselves bits of syntactic structure giving their meanings. The Stoics held the same view and maintained moreover that every sentence has an underlying logical structure, which for them was the Aristotelian subject- predicate form. They even proposed transformational processes to derive the surface from the deep structure. The idea of a semantically analytic logical form underlying the sentences of every language kept reappearing in various guises at various times. Quite recently it re-emerged under the name of generative semantics.

Abstract

Computational models can reflect the complexity of human behaviour by implementing multiple constraints within their architecture, and/or by taking into account the variety and richness of the environment to which the human is responding. We explore the second alternative in a model of word recognition that learns to map spoken words to visual and semantic representations of the words’ concepts. Critically, we employ a phonological representation utilising coarse-coding of the auditory stream, to mimic early stages of language development that are not dependent on individual phonemes to be isolated in the input, which may be a consequence of literacy development. The model was tested at different stages during training, and was able to simulate key behavioural features of word recognition in children: a developing effect of semantic information as a consequence of language learning, and a small but earlier effect of phonological information on word processing. We additionally tested the role of visual information in word processing, generating predictions for behavioural studies, showing that visual information could have a larger effect than semantics on children’s performance, but that again this affects recognition later in word processing than phonological information. The model also provides further predictions for performance of a mature word recognition system in the absence of fine-coding of phonology, such as in adults who have low literacy skills. The model demonstrated that such phonological effects may be reduced but are still evident even when multiple distractors from various modalities are present in the listener’s environment. The model demonstrates that complexity in word recognition can emerge from a simple associative system responding to the interactions between multiple sources of information in the language learner’s environment.

Abstract

The current study examines, for the first time, the viewpoint preferences of signing children in expressing spatial relations that require imposing a viewpoint (left-right, front-behind). We elicited spatial descriptions from deaf children (4–9 years of age) acquiring Turkish Sign Language (TİD) natively from their deaf parents and from adult native signers of TİD. Adults produced these spatial descriptions from their own viewpoint and from that of their addressee depending on whether the objects were located on the lateral or the sagittal axis. TİD-acquiring children, on the other hand, described all spatial configurations from their own viewpoint. Differences were also found between children and adults in the type of linguistic devices and how they are used to express such spatial relations.

Abstract

Previous studies show that children do not become adult-like in learning to set the scene and introduce referents in their narrations until 9 years of age and even beyond. However, they investigated spoken languages, thus we do not know much about how these skills are acquired in sign languages, where events are expressed in visually similar ways to the real world events, unlike in spoken languages. The results of the current study demonstrate that deaf children (3;5–9;10 years) acquiring Turkish Sign Language, and hearing children (3;8–9;11 years) acquiring spoken Turkish both acquire scene-setting and referent introduction skills at similar ages. Thus the modality of the language being acquired does not have facilitating or hindering effects in the development of these skills.

Abstract

Word learning happens in everyday contexts with many words and many potential referents for those words in view at the same time. It is challenging for young learners to find the correct referent upon hearing an unknown word at the moment. This problem of referential uncertainty has been deemed as the crux of early word learning (Quine, 1960). Recent empirical and computational studies have found support for a statistical solution to the problem termed cross-situational learning. Cross-situational learning allows learners to acquire word meanings across multiple exposures, despite each individual exposure is referentially uncertain. Recent empirical research shows that infants, children and adults rely on cross-situational learning to learn new words (Smith & Yu, 2008; Suanda, Mugwanya, & Namy, 2014; Yu & Smith, 2007). However, researchers have found evidence supporting two very different theoretical accounts of learning mechanisms: Hypothesis Testing (Gleitman, Cassidy, Nappa, Papafragou, & Trueswell, 2005; Markman, 1992) and Associative Learning (Frank, Goodman, & Tenenbaum, 2009; Yu & Smith, 2007). Hypothesis Testing is generally characterized as a form of learning in which a coherent hypothesis regarding a specific word-object mapping is formed often in conceptually constrained ways. The hypothesis will then be either accepted or rejected with additional evidence. However, proponents of the Associative Learning framework often characterize learning as aggregating information over time through implicit associative mechanisms. A learner acquires the meaning of a word when the association between the word and the referent becomes relatively strong. In this chapter, we consider these two psychological theories in the context of cross-situational word-referent learning. By reviewing recent empirical and cognitive modeling studies, our goal is to deepen our understanding of the underlying word learning mechanisms by examining and comparing the two theoretical learning accounts.