Publications

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

E-Prime® is the leading software suite by Psychology Software Tools for designing and running Psychology lab experiments. The E-Primer is the perfect accompanying guide: It provides all the necessary knowledge to make E-Prime accessible to everyone. You can learn the tools of Psychological science by following the E-Primer through a series of entertaining, step-by-step recipes that recreate classic experiments. The updated E-Primer expands its proven combination of simple explanations, interesting tutorials and fun exercises, and makes even the novice student quickly confident to create their dream experiment.

Abstract

Metaphor allows us to think and talk about one thing in terms of another, ratcheting up our cognitive and expressive capacity. It gives us concrete terms for abstract phenomena, for example, ideas become things we can grasp or let go of. Perceptual experience—characterised as physical and relatively concrete—should be an ideal source domain in metaphor, and a less likely target. But is this the case across diverse languages? And are some sensory modalities perhaps more concrete than others? This volume presents critical new data on perception metaphors from over 40 languages, including many which are under-studied. Aside from the wealth of data from diverse languages—modern and historical; spoken and signed—a variety of methods (e.g., natural language corpora, experimental) and theoretical approaches are brought together. This collection highlights how perception metaphor can offer both a bedrock of common experience and a source of continuing innovation in human communication

Abstract

When people request information, they have a variety of means for eliciting the information. In English two of the primary resources for eliciting information include asking questions, making statements about their interlocutor (thereby generating confirmation or revision). But within these types there are a variety of ways that these information elicitors can be designed. The goal of this task is to examine how different languages seek and provide information, the extent to which syntax vs prosodic resources are used (e.g., in questions), and the extent to which the design of information seeking actions and their responses display a structural preference to promote social solidarity.

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

This work presents a salvage grammar of the Biri language of Eastern Central Queensland, a Pama-Nyungan language belonging to the large Maric subgroup. As the language is no longer used, the grammatical description is based on old written sources and on recordings made by linguists in the 1960s and 1970s. Biri is in many ways typical of the Pama-Nyungan languages of Southern Queensland. It has split case marking systems, marking nouns according to an ergative/absolutive system and pronouns according to a nominative/accusative system. Unusually for its area, Biri also has bound pronouns on its verb, cross-referencing the person, number and case of core participants. As far as it is possible, the grammatical discussion is ‘theory neutral’. The first four chapters deal with the phonology, morphology, and syntax of the language. The last two chapters contain a substantial discussion of Biri’s place in the Pama-Nyungan family. In chapter 6 the numerous dialects of the Biri language are discussed. In chapter 7 the close linguistic relationship between Biri and the surrounding languages is examined.

Abstract

In this chapter, I review my EEG research on comprehending sentences in context from a pragmatics-oriented perspective. The review is organized around four questions: (1) When and how do extra-sentential factors such as the prior text, identity of the speaker, or value system of the comprehender affect the incremental sentence interpretation processes indexed by the so-called N400 component of the ERP? (2) When and how do people identify the referents for expressions such as “he” or “the review”, and how do referential processes interact with sense and syntax? (3) How directly pragmatic are the interpretation-relevant ERP effects reported here? (4) Do readers and listeners anticipate upcoming information? One important claim developed in the chapter is that the well-known N400 component, although often associated with ‘semantic integration’, only indirectly reflects the sense-making involved in structure-sensitive dynamic composition of the type studied in semantics and pragmatics. According to the multiple-cause intensified retrieval (MIR) account -- essentially an extension of the memory retrieval account proposed by Kutas and colleagues -- the amplitude of the word-elicited N400 reflects the computational resources used in retrieving the relatively invariant coded meaning stored in semantic long-term memory for, and made available by, the word at hand. Such retrieval becomes more resource-intensive when the coded meanings cued by this word do not match with expectations raised by the relevant interpretive context, but also when certain other relevance signals, such as strong affective connotation or a marked delivery, indicate the need for deeper processing. The most important consequence of this account is that pragmatic modulations of the N400 come about not because the N400 at hand directly reflects a rich compositional-semantic and/or Gricean analysis to make sense of the word’s coded meaning in this particular context, but simply because the semantic and pragmatic implications of the preceding words have already been computed, and now define a less or more helpful interpretive background within which to retrieve coded meaning for the critical word.

Abstract

The linguistic category of irrealis does not show stable semantics across languages. This makes it difficult to formulate general statements about this category, and it has led some researchers to reject irrealis as a cross-linguistically valid category. In this paper we look at the semantics of the irrealis category of Yurakaré, an unclassified language spoken in central Bolivia, and compare it to irrealis semantics of a number of other languages. Languages differ with respect to the subcategories they subsume under the heading of irrealis. The variable subcategories are future tense, imperatives, negatives, and habitual aspect. We argue that the cross-linguistic variation is not random, and can be stated in terms of an implicational scale.

Abstract

The seemingly effortless switching between languages and the merging of two languages into a coherent utterance is a hallmark of bilingual language processing, and reveals the flexibility of human speech and skilled cognitive control. That skill appears to be available not only to speakers when they produce language-switched utterances, but also to listeners and readers when presented with mixed language information. In this chapter, we review electrophysiological studies in which Event-Related Potentials (ERPs) are derived from recordings of brain activity to examine the neurocognitive aspects of comprehending and producing mixed language. Topics we discuss include the time course of brain activity associated with language switching between single stimuli and language switching of words embedded in a meaningful sentence context. The majority of ERP studies report that switching between languages incurs neurocognitive costs, but –more interestingly- ERP patterns differ as a function of L2 proficiency and the amount of daily experience with language switching, the direction of switching (switching into L2 is typically associated with higher switching costs than switching into L1), the type of language switching task, and the predictability of the language switch. Finally, we outline some future directions for this relatively new approach to the study of language switching.

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.