VROAV: Using Iconicity to Visually Represent Abstract Verbs

Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), pages 6057–6062 Marseille, 11–16 May 2020 c⃝ European Language Resources Association (ELRA), licensed under CC-BY-NC 6057 VROAV: Using Iconicity to Visually Represent Abstract Verbs Simone Scicluna1, Carlo Strapparava2 1 University of Trento Trento, Italy 2 Fondazione Bruno Kessler Via Sommarive 18, 38123 - Trento, Italy simonescicluna@gmail.com, strappa@fbk.eu Abstract Abstractness is a feature of semantics that limits our ability to visualise every conceivable concept represented by a word. By tapping into the visual representation of words, we explore the common semantic elements that link words to each other. Visual languages like sign languages have been found to reveal enlightening patterns across signs of similar meanings, pointing towards the possibility of identifying clusters of iconic meanings in words. Thanks to this insight, along with an understanding of verb predicates achieved from VerbNet, this study produced VROAV (Visual Representation of Abstract Verbs): a novel verb classification system based on the shape and movement of verbs. The outcome includes 20 classes of abstract verbs and their visual representations, which were tested for validity in an online survey. Considerable agreement between participants, who judged graphic animations based on representativeness, suggests a positive way forward for this proposal, which may be developed as a language learning aid in educational contexts or as a multimodal language comprehension tool for digital text. Keywords: Abstract verbs, verb classification, sign language, language comprehension, visual shape of words, symbolic modeling, computer-aided learning (CAL). 1. Introduction The way we see the world can be expressed using a myr- iad of words offered by the vocabulary of the language we speak in. Language vocabularies leave us with an infinity of choices to make and this is largely due to the fact that we have different words with similar meanings. While enrich- ing our views of the world, this characteristic also makes language an incredibly complex skill. Children start to ac- quire the ability to label objects around them when young, and gradually, expand their lexicon based on their lived ex- periences. This lexicon continues to expand as they learn new ways of expressing varying degrees of the same con- cept - an idea better known as synonymy. This skill allows humans to express themselves in more complex ways, such as in communicating ideas, opinions and arguments. This inevitably introduces a greater use of abstract words, which comes with challenges such as the lack of reliance of men- tal images for words and concepts. In the current study, the latter claim is not taken as a limi- tation, but rather as a motivation to delve into the existing structures humans may be utilising to more efficiently ac- cess these concepts from memory, even when they are ab- stract. So far, brain research has offered insight on the fact that we develop mental images for words learned. However, what this fails to tell us is how they would look like visu- ally. One way of obtaining this is to observe how humans react …

Content truncated to 500 words