{"pk":27153,"title":"A Neural Network Model for Taxonomic Responding with Realistic Visual Inputs","subtitle":null,"abstract":"We propose a neural network model that accounts for the emer-gence of the taxonomic constraint in early word learning. Ourproposal is based on Mayor and Plunkett (2010)’s neurocom-putational model of the taxonomic constraint and overcomesone of its limitations, namely the fact that it considers arti-ficially built, simplified stimuli. In fact, while in the originalmodel the visual stimuli are random, sparse dot patterns, in ourproposed solution they are photographic images from the Im-ageNet database. In our model the represented objects in theimage can be of different size, color, location in the picture,point of view, etc.. We show that, notwithstanding the aug-mented complexity in the input, the proposed model comparesfavorably with respect to Mayor and Plunkett (2010)’s model.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Posters: Papers","is_remote":true,"remote_url":"https://escholarship.org/uc/item/1vg4s7j2","frozenauthors":[{"first_name":"Giorgia","middle_name":"","last_name":"Fenoglio","name_suffix":"","institution":"University of Torino","department":""},{"first_name":"Roberto","middle_name":"","last_name":"Esposito","name_suffix":"","institution":"University of Torino","department":""},{"first_name":"Valentina","middle_name":"","last_name":"Gliozzi","name_suffix":"","institution":"University of Torino","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2017-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/27153/galley/16789/download/"}]}