{"type":"ScholarlyArticle","title":"Phonovisual Biases in Language: is the Lexicon Tied to the Visual World?","authors":[{"name":"Andrea Gregor de Varda","slug":"andrea-gregor-de-varda","given":"Andrea Gregor","family":"de Varda","affiliation":""},{"name":"Carlo Strapparava","slug":"carlo-strapparava","given":"Carlo","family":"Strapparava","affiliation":""}],"abstract":"The present paper addresses the study of cross-linguistic and cross-modal iconicity within a deep learning framework. An LSTM-based Recurrent Neural Network is trained to associate the phonetic representation of a concrete word, encoded as a sequence of feature vectors, to the visual representation of its referent, expressed as an HCNN-transformed image. The processing network is then tested, without further training, in a language that does not appear in the training set and belongs to a different language family. The performance of the model is evaluated through a comparison with a randomized baseline; we show that such an imaginative network is capable of extracting language-independent generalizations in the mapping from linguistic sounds to visual features, providing empirical support for the hypothesis of a universal sound-symbolic substrate underlying all languages.","doi":"10.24963/ijcai.2021/89","url":"https://ijcai.org/proceedings/2021/89","pdf":"https://ijcai.org/proceedings/2021/0089.pdf","markdown":"https://ijcai.org/proceedings/2021/89.md","bibtex":"https://ijcai.org/proceedings/2021/bibtex/89","volume":{"slug":"2021","title":"Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2021","url":"https://ijcai.org/proceedings/2021/","year":2021,"location":"Montreal","dates":"19-27 August 2021","editors":"Prof. Zhi-Hua Zhou","isbn":"978-0-9992411-9-6","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2021"},"section":"Computer Vision I","track":"Main Track","number":89,"pages":{"first":643,"last":649},"keywords":["Computer Vision: Language and Vision","Natural Language Processing: Psycholinguistics","Natural Language Processing: Phonology, Morphology, and Word Segmentation"],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}