Katherine Elizabeth Twomey

Do as I say, not as I do: A lexical distributional account of English locative verb class acquisition

Children overgeneralise verbs to ungrammatical structures early in acquisition, but retreat from these overgeneralisations as they learn semantic verb classes. In a large corpus of English locative utterances (e.g., the woman sprayed water onto the wall/wall with water), we found structural biases which changed over development and which could explain overgeneralisation behaviour. Children and adults had similar verb classes and a correspondence analysis suggested that lexical distributional regularities in the adult input could help to explain the acquisition of these classes. A connectionist model provided an explicit account of how structural biases could be learned over development and how these biases could be reduced by learning verb classes from distributional regularities.

Preemption versus Entrenchment: Towards a Construction-General Solution to the Problem of the Retreat from Verb Argument Structure Overgeneralization.

Participants aged 5;2-6;8, 9;2-10;6 and 18;1-22;2 (72 at each age) rated verb argument structure overgeneralization errors (e.g., *Daddy giggled the baby) using a five-point scale. The study was designed to investigate the feasibility of two proposed construction-general solutions to the question of how children retreat from, or avoid, such errors. No support was found for the prediction of the preemption hypothesis that the greater the frequency of the verb in the single most nearly synonymous construction (for this example, the periphrastic causative; e.g., Daddy made the baby giggle), the lower the acceptability of the error. Support was found, however, for the prediction of the entrenchment hypothesis that the greater the overall frequency of the verb, regardless of construction, the lower the acceptability of the error, at least for the two older groups. Thus while entrenchment appears to be a robust solution to the problem of the retreat from error, and one that generalizes across different error types, we did not find evidence that this is the case for preemption. The implication is that the solution to the retreat from error lies not with specialized mechanisms, but rather in a probabilistic process of construction competition.

What's on the Inside Counts: A Grounded Account of Concept Acquisition and Development

Understanding the factors which affect the age of acquisition (AoA) of words and concepts is fundamental to understanding cognitive development more broadly. Traditionally, studies of AoA have taken two approaches, either exploring the effect of linguistic variables such as input frequency (e.g., Naigles and Hoff-Ginsberg, 1998) or the semantics of the underlying concept, such as concreteness or imageability (e.g., Bird et al., 2001). Embodied theories of cognition, meanwhile, assume that concepts, even relatively abstract ones, can be grounded in the embodied experience. While the focus of such discussions has been mainly on grounding in external modalities, more recently some have argued for the importance of interoceptive features, or grounding in complex modalities such as social interaction. In this paper, we argue for the integration and extension of these two strands of research. We demonstrate that the psycholinguistic factors traditionally considered to determine AoA are far from sufficient to account for the variability observed in AoA data. Given this gap, we propose groundability as a new conceptual tool that can measure the degree to which concepts are grounded both in external and, critically, internal modalities. We then present a mechanistic theory of conceptual representation that can account for groundability in addition to the existing variables argued to influence concept acquisition in both the developmental and embodied cognition literatures, and discuss its implications for future work in concept and cognitive development.

Lexical distributional cues, but not situational cues, are readily used to learn abstract locative verb-structure associations.

Children must learn the structural biases of locative verbs in order to avoid making overgeneralisation errors (e.g., (∗)I filled water into the glass). It is thought that they use linguistic and situational information to learn verb classes that encode structural biases. In addition to situational cues, we examined whether children and adults could use the lexical distribution of nouns in the post-verbal noun phrase of transitive utterances to assign novel verbs to locative classes. In Experiment 1, children and adults used lexical distributional cues to assign verb classes, but were unable to use situational cues appropriately. In Experiment 2, adults generalised distributionally-learned classes to novel verb arguments, demonstrating that distributional information can cue abstract verb classes. Taken together, these studies show that human language learners can use a lexical distributional mechanism that is similar to that used by computational linguistic systems that use large unlabelled corpora to learn verb meaning.

Curiosity-based learning in infants : A neurocomputational approach

Abstract Infants are curious learners who drive their own cognitive development by imposing structure on their learning environment as they explore. Understanding the mechanisms by which infants structure their own learning is therefore critical to our understanding of development. Here we propose an explicit mechanism for intrinsically motivated information selection that maximizes learning. We first present a neurocomputational model of infant visual category learning, capturing existing empirical data on the role of environmental complexity on learning. Next we “set the model free”, allowing it to select its own stimuli based on a formalization of curiosity and three alternative selection mechanisms. We demonstrate that maximal learning emerges when the model is able to maximize stimulus novelty relative to its internal states, depending on the interaction across learning between the structure of the environment and the plasticity in the learner itself. We discuss the implications of this new curiosity mechanism for both existing computational models of reinforcement learning and for our understanding of this fundamental mechanism in early development.

All the Right Noises: Background Variability Helps Early Word Learning

Abstract Variability is prevalent in early language acquisition, but, whether it supports or hinders learning is unclear; while target variability has been shown to facilitate word learning, variability in competitor items has been shown to make the task harder. Here, we tested whether background variability could boost learning in a referent selection task. Two groups of 2‐year‐old children saw arrays of one novel and two known objects on a screen, and they heard a novel or known label. Stimuli were identical across conditions, with the exception that in the constant color condition objects appeared on a uniform white background, and in the variable color condition backgrounds were different, uniform colors. At test, only children in the variable condition showed evidence of retaining label‐object associations. These data support findings from the adult memory literature, which suggest that variability supports learning by decontextualizing representations. We argue that these data are consistent with dynamic systems accounts of learning in which low‐level entropy adds sufficient noise to the developmental system to precipitate a change in behavior.

Learned Labels Shape Pre-speech Infants’ Object Representations

Infants rapidly learn both linguistic and nonlinguistic representations of their environment and begin to link these from around 6 months. While there is an increasing body of evidence for the effect of labels heard in‐task on infants’ online processing, whether infants’ learned linguistic representations shape learned nonlinguistic representations is unclear. In this study 10‐month‐old infants were trained over the course of a week with two 3D objects, one labeled, and one unlabeled. Infants then took part in a looking time task in which 2D images of the objects were presented individually in a silent familiarization phase, followed by a preferential looking trial. During the critical familiarization phase, infants looked for longer at the previously labeled stimulus than the unlabeled stimulus, suggesting that learning a label for an object had shaped infants’ representations as indexed by looking times. We interpret these results in terms of label activation and novelty response accounts and discuss implications for our understanding of early representational development.

Word for word

How well children learn words is influenced by many things, including the environment and the manner in which adults speak to them. Communication experts Dr Rebecca Frost, Dr Katherine Twomey, Dr Gemma Taylor, Professor Gert Westermann and Professor Padraic Monaghan explain