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

Multimodal integration is a central characteristic of human cognition. However our understanding of the interaction between modalities and its influence on behaviour is still in its infancy. This paper examines the value of the Hub & Spoke framework (Plaut, 2002; Rogers et al., 2004; Dilkina et al., 2008; 2010) as a tool for exploring multimodal interaction in cognition. We present a Hub and Spoke model of language–vision information interaction and report the model’s ability to replicate a range of phonological, visual and semantic similarity word-level effects reported in the Visual World Paradigm (Cooper, 1974; Tanenhaus et al, 1995). The model provides an explicit connection between the percepts of language and the distribution of eye gaze and demonstrates the scope of the Hub-and-Spoke architectural framework by modelling new aspects of multimodal cognition.

Abstract

We investigate how the lexical nature of weak definites influences the phenomenon of direct object scrambling in Dutch. Earlier experiments have indicated that weak definites are more resistant to scrambling than strong definites. We examine how the notion of weak definiteness used in this experimental work can be reduced to lexical connectedness. We explore four different ways of quantifying the relation between a direct object and the verb. Our results show that predictability of a verb given the object (verb cloze probability) provides the best fit to the weak/strong distinction used in the earlier experiments

Abstract

Left dislocation is characterized by a sentence-initial element which is crossreferenced in the remainder of the sentence, and often set off by an intonation break. Because of these properties, left dislocation has been analyzed as an extraclausal phenomenon. Whether or not left dislocation can occur within subordinate clauses has been a matter of debate in the literature, but has never been checked against corpus data. This paper presents data from Avatime, a Kwa (Niger-Congo) language spoken in Ghana, showing that left dislocation occurs within subordinate clauses in spontaneous discourse. This poses a problem for the extraclausal analysis of left dislocation. I show that this problem can best be solved by assuming that Avatime allows the embedding of units larger than a clause

Abstract

The aim of this paper is to discuss the repercussions of a conceptual orientation on two crucial parts of the Role and Reference Grammar (RRG) linking algorithm, that is, semantic representation and constructional schemas. Firstly, it is argued that adopting FunGramKB’s notion of conceptual logical structure (CLS) over standard RRG logical structures (LSs) has numerous advantages since meaning has now access to conceptual knowledge and therefore a CLS provides a format that goes beyond those aspects that are syntactically visible. The second part introduces the notion of the grammaticon, the component where constructional schemas actually reside. RRG constructional schemas are analyzed within a conceptual framework like that provided in FunGramKB. In essence, it is shown that a conceptual orientation to the RRG linking system by the addition of CLSs enriches the semantic representations in it substantially

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.