SENSE · The Bilingual SEmaNtic SystEm (SENSE): Computational Assessment of Cross-linguistic Meaning Representation Across Cultures

Growing evidence suggests lexical semantics is not universal, being shaped by culture, and translation equivalents may bear distinct meanings in each language. If so, how do bilingual brains juggle competing meaning representations for translations? SENSE will investigate the impact knowing a second language has on the native language's semantic system across cultures. To do so, we will use two recent computational approaches: distributional semantic and word association models (obtained from linguistic corpora and free association data, respectively). Both methods have shown promising results in predicting human performance in semantic tasks, making them ideal candidates to inform psychological theories. Yet, which models better reflect human semantic representation is under debate. Further, few studies in semantic memory research have used these tools. While researchers have stressed the need to adopt these methodologies, these calls almost invariably have a monolingual scope, neglecting the pressing questions bilingualism poses on the nature of the semantic system. SENSE has three overarching goals. (1) To assess the role of culture in the construction of meaning by examining the conceptual structure of languages from different primary families spoken in culturally distinct societies (Spanish, Turkish, Chinese). English, the invariable second language, will also be studied. (2) To measure bilingualism's impact on semantic representation by investigating how L2 English semantic information integrates into the already established native language's semantic systems. (3) To test which models are better suited to account for meaning representation by comparing their predictability of human performance in a battery of semantic tasks. Overall, SENSE will make a solid contribution to understanding how culture and bilingualism shape the semantic system while helping to establish modern computational techniques in cognitive psychology research.