What aspects of word meaning are important in early word learning and lexico-semantic network development? Adult lexico-semantic systems flexibly encode multiple types of semantic features, including: functional, perceptual, taxonomic, and encyclopedic. However, various theoretical accounts of lexical development differ on whether and how these semantic properties of word meanings are initially encoded into young children's emerging lexico-semantic networks. While some accounts highlight the importance of early perceptual vs. conceptual properties, others posit that thematic or functional aspects of word meaning are primary relative to taxonomic knowledge. We seek to shed light on these debates with two modeling studies that explore patterns in early word learning using a large database of early vocabulary in 5450 children, and a newly developed set of semantic features of early-acquired nouns. In study 1, we ask whether semantic properties of early-acquired words relate to order in which these words are typically learned and study 2 models normative lexico-semantic noun-feature network development compared to random network growth. Both studies provide converging evidence that perceptual properties of word meanings play a key role in early word learning and lexico-semantic network development. The findings lend support to theoretical accounts of language learning that highlight the importance of the child's perceptual experience.

The mature lexicon encodes semantic relations between words, and these connections can alternately facilitate and interfere with language processing. We explore the emergence of these processing dynamics in 18-month-olds (N = 79) using a novel approach that calculates individualized semantic structure at multiple granularities in participants’ productive vocabularies. Participants completed two interleaved eye-tracked word recognition tasks involving semantically unrelated and related picture contexts, which sought to measure the impact of lexical facilitation and interference on processing, respectively. Semantic structure and vocabulary size differentially impacted processing in each task. Category level structure facilitated word recognition in 18-month-olds with smaller productive vocabularies, while overall lexical connectivity interfered with word recognition for toddlers with relatively larger vocabularies. The results suggest that, while semantic structure at multiple granularities is measurable even in small lexicons, mechanisms of semantic interference and facilitation are driven by the development of structure at different granularities. We consider these findings in light of accounts of adult word recognition that posits that different levels of structure index strong and weak activation from nearby and distant semantic neighbors. We also consider further directions for developmental change in these patterns.

While recent research suggests that toddlers tend to learn word meanings with many “perceptual” features that are accessible to the toddler’s sensory perception, it is not clear whether and how building a lexicon with perceptual connectivity supports attention to and recognition of word meanings. We explore this question in 24–30-month-olds (N = 60) in relation to other individual differences, including age, vocabulary size, and tendencies to maintain focused attention. Participants’ looking to item pairs with high vs. low perceptual connectivity—defined as the number of words in a child’s lexicon sharing perceptual features with the item—was measured before and after target item labeling. Results revealed pre-labeling attention to known items is biased to both high- and low-connectivity items: first to high, and second, but more robustly, to low-connectivity items. Subsequent object–label processing was also facilitated for high-connectivity items, particularly for children with temperamental tendencies to maintain focused attention. This work provides the first empirical evidence that patterns of shared perceptual features within children’s known vocabularies influence both visual and lexical processing, highlighting the potential for a newfound set of developmental dependencies based on the perceptual/sensory structure of early vocabularies.

When language users predict upcoming speech, they generate pluralistic expectations, weighted by likelihood (Kuperberg & Jaeger, 2016). Many variables influence the prediction of highly likely sentential outcomes, but less is known regarding variables affecting the prediction of less-likely outcomes. Here we explore how English vocabulary size and self-identification as a native speaker (NS) of English modulate adult bi-/multilinguals’ preactivation of less-likely sentential outcomes in two visual-world experiments. Participants heard transitive sentences containing an agent, action, and theme (The pirate chases the ship) while viewing four referents varying in expectancy by relation to the agent and action. In Experiment 1 (N=70), spoken themes referred to highly expected items (e.g., ship). Results indicate lower skill (smaller vocabulary size) and less confident (not identifying as NS) bi-/multilinguals activate less-likely action-related referents more than their higher skill/confidence peers. In Experiment 2 (N=65), themes were one of two less-likely items (The pirate chases the bone/cat). Results approaching significance indicate an opposite but similar size effect: higher skill/confidence listeners activate less-likely action-related (e.g., bone) referents slightly more than lower skill/confidence listeners. Results across experiments suggest higher skill/confidence participants more flexibly modulate their linguistic predictions per the demands of the task, with similar but not identical patterns emerging when bi-/multilinguals are grouped by self-ascribed NS status versus vocabulary size.

Early language learning relies on statistical regularities that exist across timescales in infants’ lives. Two types of these statistical regularities are the routine activities that make up their day, such as mealtime and play, and the real-time repeated behaviors that make up the moment-by-moment dynamics of those routines. These two types of regularities are different in nature and are embedded at two different temporal scales, which led to divergent research in the literature – those who collect long-form recordings and observations of at-home behavior and those who use eye trackers and micro-level analyses to quantify real-time behavior in laboratories. The goal of present paper is to jointly examine and connect the statistical regularities at these two timescales. Towards this goal, we brought wearable eye trackers to English- and Spanish-speaking families’ homes to record parent and toddler visual attention during daily routines. We transcribed parent speech during object play and mealtime and coded toddler visual attention during naming moments. We found that parents and toddlers jointly interacted with the unique vocabularies of the two activities. Although naming and attention were more coordinated during object play, mealtime still afforded opportunities for high-quality naming moments. Our results lay the building blocks for connecting these two lines of research and demonstrate the feasibility of at-home data collection with eye trackers.