The Visual Representation of Abstract Verbs: Merging Verb Classification with Iconicity in Sign Language
- Simone Scicluna, University of Trento, Trento, Italy
- Carlo Strapparava, FBK-Irst, Trento, Italy
AbstractTheories like the picture superiority effect prove that visual information is vital in the acquisition of knowledge, such as in language learning. Words can be graphically represented to illustrate the meaning of a message and facilitate its understanding, but this rarely applies to abstract words. The current research turns to sign languages to explore the common semantic elements that link abstract words to each other, pointing towards the possibility of creating clusters of iconic meanings. By using sign language insight and VerbNet’s organisation of verb predicates, this study presents a novel organisation of 500 English abstract verbs classified by visual shape. Graphic animation was used to visually represent 20 classes of abstract verbs (see on www.vroav.online). An online survey was created to achieve judgements on the graphic visuals’ representativeness. Significant agreement between participants suggests a positive way forward for further research and applications within multimodal communication and computer assisted learning.
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