Analyzing individuality in vocablary deveropment using large scale infant vocabulary data

Abstract

This study elucidates the individuality of the ways in which infants acquire vocaburary and, based on this understanding, attempts to classify the vocabulary development processes. Specifically, vocabulary development data from infants with similar vocabulary sizes were used for topic analysis using Latent Dirichlet Allocation (LDA). By analyzing these topics, we investigated the individuality of the infants. Additionally, using the results, we attempted to construct Support Vector Machines (SVMs) by using the ratios of topics output for each infant's vocabulary as an input vector. Through this analysis, we examined whether there are types of individuality. Consequently, this study examines whether the process of vocabulary development in infants depends on other factors in addition to the number of words.