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

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

How do languages express ideas of movement, and how do they package features that can be part of motion, such as path and cause? This questionnaire is used to gain a picture of the lexical resources a language draws on for motion expressions. It targets issues of semantic conflation (i.e., what other semantic information besides motion may be encoded in a verb root) and patterns of semantic distribution (i.e., what types of information are encoded in the morphemes that come together to build a description of a motion event). It was originally designed for Australian languages, but has since been used around the world.

Abstract

Contrastive reference, where a speaker presents or identifies one item in explicit contrast to another (I like this book but that one is boring), has special communicative and information structure properties. This can be reflected in rules of demonstrative use. For example, in some languages, terms equivalent to this and that can be used for contrastive reference in almost any spatial context. But other two-term languages stick more closely to “distance rules” for demonstratives, allowing a this-like term in close space only. This task elicits data concerning one context of contrastive reference, focusing on whether (and how) non-proximal demonstratives can be used to distinguish objects within a proximal area. The task runs like a memory game, with the consultant being asked to identify the locations of two or three hidden items arranged within arm’s reach.

Abstract

Demonstrative terms (e.g., this and that) are key to understanding how a language constructs and interprets spatial relationships. They are tricky to pin down, typically having functions that do not match “idealized” uses, and that can become invisible in narrow elicitation settings. This questionnaire is designed to identify the range(s) of use of certain spatial demonstrative terms, and help assess the roles played by gesture, access, attention, and addressee knowledge in demonstrative use. The stimuli consist of 25 diagrammed “elicitation settings” to be created by the researcher.

Abstract

Angelika Wittek untersuchte Zustandsveränderungsverben bei vier- bis sechsjährigen Kindern. Englischsprechende Kinder verstehen bis zum Alter von 8 Jahren diese Verben als Bewegungsverben und ignorieren, daß sie zusätzlich die Information über einen Endzustand im Sinne der Negation des Ausgangszustands beeinhalten. Wittek zeigte, daß entgegen der Erwartung transparente, morphologisch komplexe Formen (wachmachen), in denen die Partikel den Endzustand explizit macht, nicht besser verstanden werden als Simplizia (wecken). Zudem diskutierte sie, inwieweit die Verwendung des Adverbs wieder in restitutiver Lesart Hinweise auf den Erwerb dieser Verben geben kann.

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.