Modeling bilingual word associations as connected monolingual networks

Yevgen Matusevych, Amir Ardalan Kalantari Dehaghi, Suzanne Stevenson

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Word associations are a common tool in research on the mental lexicon. Studies report that bilinguals produce different word associations in their non-native language than monolinguals, and propose at least three mechanisms responsible for this difference: bilinguals may rely on their native associations (through translation), on collocational patterns, and on the phonological similarity between words. In this paper, we first test the differences between monolingual and bilingual responses, showing that these differences are consistent and significant. Second, we present a computational model of bilingual word associations, implemented as a semantic network paired with a retrieval mechanism. Our model predicts bilingual word associations better than monolingual baselines, and translation is the main mechanism explaining its
success, while collocational and phonological associations do not improve the model.
Original languageEnglish
Title of host publicationProceedings of the 8th Workshop on Cognitive Modeling and Computational Linguistics (CMCL 2018)
EditorsAsad Sayeed, Cassandra Jacobs, Tal Linzen, Martin van Schijndel
PublisherAssociation for Computational Linguistics
Number of pages11
Publication statusPublished - 7 Jan 2018
EventCognitive Modeling and Computational Linguistics (CMCL) 2018 - Salt Lake City, United States
Duration: 7 Jan 2018 → …


WorkshopCognitive Modeling and Computational Linguistics (CMCL) 2018
Abbreviated titleCMCL 2018
Country/TerritoryUnited States
CitySalt Lake City
Period7/01/18 → …
Internet address


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