The Multilink model for word translation: Similarity effects in word recognition and word translation

Simple item page
dc.contributor.advisorDijkstra, A.F.J.
dc.contributor.advisorWahl, A.R.
dc.contributor.authorHalem, N.A. van
dc.date.issued2016-07-19
dc.description.abstractThe Multilink Model for word translation is developed by Dijkstra & Rekké (2012). We have made several adaptations to the model in order to make it fit the data better and to make it more psychologically plausible. I have tested the performance of the improved model on both word recognition tasks as well as on word translation tasks. I have primarily looked at the cognacy effect and the effect of word length on reaction time. Most results I have found are well in line with the literature; cognates are recognised and translated considerably faster than other words. False friends still are a problem for Multilink.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/1878
dc.language.isoenen_US
dc.thesis.facultyFaculteit der Sociale Wetenschappenen_US
dc.thesis.specialisationBachelor Artificial Intelligenceen_US
dc.thesis.studyprogrammeArtificial Intelligenceen_US
dc.thesis.typeBacheloren_US
dc.titleThe Multilink model for word translation: Similarity effects in word recognition and word translationen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Halem, N._BSc_Thesis_2016.pdf
Size:
1.84 MB
Format:
Adobe Portable Document Format
Description:
Thesis text
Download
Collections
Faculteit der Sociale Wetenschappen