Publications

Abstract

We argue that language learning occurs in triadic interactions, where caregivers and children engage not only with each other but also with objects, actions and non-verbal cues that shape language acquisition. We illustrate this using two studies on real-time interactions in spoken and signed language. The first examines shared book reading, showing how caregivers use speech, gestures and gaze coordination to establish joint attention, facilitating word-object associations. The second study explores joint attention in spoken and signed interactions, demonstrating that signing dyads rely on a wider range of multimodal behaviours – such as touch, vibrations and peripheral gaze – compared to speaking dyads. Our data highlight how different language modalities shape attentional strategies. We advocate for research that fully incorporates the dynamic interplay between language, attention and environment.

Abstract

In order to understand early word learning we need to better understand and quantify properties of the input that young children receive. We extended the human simulation paradigm (HSP) using egocentric videos taken from infant head-mounted cameras. The videos were further annotated with gaze information indicating in-the-moment visual attention from the infant. Our new HSP prompted participants for two types of responses, thus differentiating referential from semantic ambiguity in the learning input. Consistent with findings on visual attention in word learning, we find a strongly bimodal distribution over HSP accuracy. Even in this open-ended task, most videos only lead to a small handful of common responses. What's more, referential ambiguity was the key bottleneck to performance: participants can nearly always recover the exact word that was said if they identify the correct referent. Finally, analysis shows that adult learners relied on particular, multimodal behavioral cues to infer those target referents.

Abstract

In the word-learning domain, both adults and young children are able to find the correct referent of a word from highly ambiguous contexts that involve many words and objects by computing distributional statistics across the co-occurrences of words and referents at multiple naming moments (Yu & Smith, 2007; Smith & Yu, 2008). However, there is still debate regarding how learners accumulate distributional information to learn object labels in natural learning environments, and what underlying learning mechanism learners are most likely to adopt. Using the Human Simulation Paradigm (Gillette, Gleitman, Gleitman & Lederer, 1999), we found that participants’ learning performance gradually improved and that their ability to remember and carry over partial knowledge from past learning instances facilitated subsequent learning. These results support the statistical learning model that word learning is a continuous process.