Publications

Abstract

Incremental sentence generation imposes special constraints on the representation of the grammar and the design of the formulator (the module which is responsible for constructing the syntactic and morphological structure). In the model of natural speech production presented here, a formalism called Segment Grammar is used for the representation of linguistic knowledge. We give a definition of this formalism and present a formulator design which relies on it. Next, we present an object- oriented implementation of Segment Grammar. Finally, we compare Segment Grammar with other formalisms.

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

Ook al hebben we het niet altijd door, onze zintuigen werken altijd samen. Als je iemand ziet praten, bijvoorbeeld, verwerken je hersenen automatisch tegelijkertijd het geluid van de woorden en de bewegingen van de lippen. Omdat onze zintuigen altijd samenwerken zijn onze hersenen erg gevoelig voor dingen die ‘samenhoren’ en goed bij elkaar passen. In dit hoofdstuk beschrijven we een project onderzoekend leren met als thema ‘Samenwerkende zintuigen’.

Abstract

In this chapter we introduce the CLARIN Knowledge Centre for Atypical Communication Expertise. The mission of ACE is to support researchers engaged in languages which pose particular challenges for analysis; for this, we use the umbrella term “atypical communication”. This includes language use by second-language learners, people with language disorders or those suffering from lan-guage disabilities, and languages that pose unique challenges for analysis, such as sign languages and languages spoken in a multilingual context. The chapter presents details about the collaborations and outreach of the centre, the services offered, and a number of showcases for its activities.

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.