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Recent work has shown that distributed word representations can encodeabstract information from child-directed speech. In this paper, we usediachronic distributed word representations to perform temporal modeling andanalysis of lexical development in children. Unlike all previous work, we usetemporally sliced corpus to learn distributed word representations ofchild-speech and child-directed speech under a curriculum-learning setting. Inour experiments, we perform a lexical categorization task to plot the semanticand syntactic knowledge acquisition trajectories in children. Next, we performlinear mixed-effects modeling over the diachronic representational changes tostudy the role of input word frequencies in the rate of word acquisition inchildren. We also perform a fine-grained analysis of lexical knowledge transferfrom adults to children using Representational Similarity Analysis. Finally, weperform a qualitative analysis of the diachronic representations from ourmodel, which reveals the grounding and word associations in the mental lexiconof children. Our experiments demonstrate the ease of usage and effectiveness ofdiachronic distributed word representations in modeling lexical development.

Towards Using Diachronic Distributed Word Representations as Models of Lexical Development