Global and Local Feature Distinctiveness Effects in Language Acquisition

Abstract

Various aspects of semantic features drive early vocabulary development, but less is known about how the global and local structure of the overall semantic feature space influences language acquisition. A feature network of English words was constructed from a large database of adult feature production norms such that edges in the network represented feature distances between words (i.e., Manhattan distances of probability distributions of features elicited for each pair of words). A word's global feature distinctiveness is measured with respect to all other words in the network and a word's local feature distinctiveness is measured relative to words in sub-networks derived from clustering analyses. This paper investigates how feature distinctiveness of individual words at local and global scales of the network influences language acquisition. Regression analyses indicate that global feature distinctiveness was associated with earlier age of acquisition ratings, and was a stronger predictor of age of acquisition than local feature distinctiveness. These results suggest that the global structure of the semantic feature network could play an important role in language acquisition, whereby globally distinctive concepts help to structure vocabulary development over the lifespan.

Investigating preferential acquisition and attachment in early word learning through cognitive, visual and latent multiplex lexical networks

“…We combine up to 7 network layers representing semantic, phonological, visual, sensorimotor and latent aspects of words, and 2 word embeddings, like GloVe (latent word features [42]) and words-as-classifiers (i.e, visual word features [43]), compar-ing networked and vectorial features of conceptual similarities. Results indicate that: (i) preferential attachment can capture signals of typical word learning but only when visual and latent aspects of words are merged in the same multiplex network containing semantic/syntactic/phonological layers; (ii) preferential acquisition produces stronger signals in all other cases, confirming past studies [44,16,12,13]; (iii) word distinctiviness is consistently found across word learning strategies and windows of cognitive development, extending results from past approaches [45,46].…”

“…We interpret these anti-correlations as additional evidence that conceptual similarity can drive early word acquisition in toddlers [13,12,14,44] but in synergy with conceptual distinctiveness; i.e., how distinct a given concept appears in comparison to its reference context. Recent studies [45,46] pointed out how semantic distinctiveness over semantic features was a good predictor of adult-reported AoA norms, with global feature distinctiveness associated with earlier AoA ratings. Our results, over child-reported typical learning trajectories, confirm the presence of distinctiveness contributing to even early word acquisition, extending results from previous investigations [45,46].…”

“…Recent studies [45,46] pointed out how semantic distinctiveness over semantic features was a good predictor of adult-reported AoA norms, with global feature distinctiveness associated with earlier AoA ratings. Our results, over child-reported typical learning trajectories, confirm the presence of distinctiveness contributing to even early word acquisition, extending results from previous investigations [45,46]. Our results suggest that feature distinctiveness is strongly mediated by visual cues and latent aspects of language, as it was also found by Engelthaler and Hills within a different framework [45].…”

Feature-rich multiplex lexical networks reveal mental strategies of early language learning

“…Future enhancements of random-walk models should account also for distinctiveness in addition to similarity. The recent work by Siew 60 indicates that global feature distinctiveness, i.e. how many different semantic features are possessed by a word, correlates with earlier acquisition.…”