Abstract
For a long time, philosophers, linguists and scientists have been keen on finding an answer to the mind-bending question “what does abstract language look like?”, which has also sprung from the phenomenon of mental imagery and how this emerges in the mind. One way of approaching the matter of word representations is by exploring 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. With this insight, merged with an understanding of verb predicates achieved from VerbNet, this study presents a novel verb classification system based on visual shapes, using graphic animation to visually represent 20 classes of abstract verbs. Considerable agreement between participants who judged the 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.- Anthology ID:
- 2020.lrec-1.742
- Volume:
- Proceedings of the Twelfth Language Resources and Evaluation Conference
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 6057–6062
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.742
- DOI:
- Cite (ACL):
- Simone Scicluna and Carlo Strapparava. 2020. VROAV: Using Iconicity to Visually Represent Abstract Verbs. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 6057–6062, Marseille, France. European Language Resources Association.
- Cite (Informal):
- VROAV: Using Iconicity to Visually Represent Abstract Verbs (Scicluna & Strapparava, LREC 2020)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2020.lrec-1.742.pdf