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{ "pk": 28815, "title": "Statistical Learning of Conjunctive Probabilities", "subtitle": null, "abstract": "Most statistical learning studies focus on the learning oftransitional probabilities between adjacent elements in asequence, however, other statistical regularities may un-derpin different aspects of processing language and regu-larities in other domains. Here, we investigate how con-junctive statistical regularities (of the form A and B to-gether predict C) can be learned, and how this learningis impacted by similarity in representations analogousto that in unambiguous words, homonyms with mul-tiple unrelated meanings, and polysemes with multiplerelated meanings. We observed that provided the stimu-lus structure is relatively simple, participants are readilyable to learn conjunctive probabilities and display sen-sitivity to relatedness among representations. These re-sults open new theoretical possibilities for exploring thedomain-generality of how the learning and processingsystems merge conjunctive information in simple labo-ratory tasks and in natural language.", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [ { "word": "Statistical Learning; Lexical Ambiguity;Transitional Probability; Conjunctive Probability" } ], "section": "Papers with Poster Presentations", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/0nf5q4gd", "frozenauthors": [ { "first_name": "Di", "middle_name": "", "last_name": "Mo", "name_suffix": "", "institution": "University of Toronto", "department": "" }, { "first_name": "Blair", "middle_name": "C.", "last_name": "Armstrong", "name_suffix": "", "institution": "University of Toronto", "department": "" } ], "date_submitted": null, "date_accepted": null, "date_published": "2019-01-01T18:00:00Z", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28815/galley/18686/download/" } ] }