TY - JOUR AU - Soeteman, Arie AU - Gutierrez, Dario AU - Bruni, Elia AU - Shutova, Ekaterina PY - 2020/04/03 Y2 - 2024/03/28 TI - Modelling Form-Meaning Systematicity with Linguistic and Visual Features JF - Proceedings of the AAAI Conference on Artificial Intelligence JA - AAAI VL - 34 IS - 05 SE - AAAI Technical Track: Natural Language Processing DO - 10.1609/aaai.v34i05.6416 UR - https://ojs.aaai.org/index.php/AAAI/article/view/6416 SP - 8870-8877 AB - <p>Several studies in linguistics and natural language processing (NLP) pointed out systematic correspondences between word form and meaning in language. A prominent example of such systematicity is iconicity, which occurs when the form of a word is motivated by some perceptual (e.g. visual) aspect of its referent. However, the existing data-driven approaches to form-meaning systematicity modelled word meanings relying on information extracted from textual data alone. In this paper, we investigate to what extent our visual experience explains some of the form-meaning systematicity found in language. We construct word meaning representations from linguistic as well as visual data and analyze the structure and significance of form-meaning systematicity found in English using these models. Our findings corroborate the existence of form-meaning systematicity and show that this systematicity is concentrated in localized clusters. Furthermore, applying a multimodal approach allows us to identify new patterns of systematicity that have not been previously identified with the text-based models.</p> ER -