Bridging the Gap between Graph Modeling and Developmental Psycholinguistics: An Experiment on Measuring Lexical Proximity in Chinese Semantic Space

Modeling of semantic space is a new and challenging research topic both in cog- nitive science and linguistics. Existing approaches can be classified into two different types according to how the calculation are done: either a word-by-word co-occurrence matrix or a word-by-context matrix (Riordan 2007). In this paper, we argue that the existing popular distributional semantic model (vector space model), does not adequately explain the age-of- acquisition data in Chinese. An alternatively measure of semantic proximity called PROX (Gaume et al, 2006) is applied instead. The application or PROX has interesting psycholin- guistic implications. Unlike previous semantic space models, PROX can be trained with children's data as well as adult data. This allows us to test the hypothesis that children's se- mantic space approximates the target of acquisition: adult's semantic space. It also allows us to compare our Chinese experiment results with French results to see to attest the universality of the approximation model.