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{ "pk": 28176, "title": "Modeling garden path effects without explicit hierarchical syntax", "subtitle": null, "abstract": "The disambiguation of syntactically ambiguous sentences canlead to reading difficulty, often referred to as a garden path ef-fect. The surprisal hypothesis suggests that this difficulty canbe accounted for using word predictability. We tested this hy-pothesis using predictability estimates derived from two fam-ilies of language models: grammar-based models, which ex-plicitly encode the syntax of the language; and recurrent neuralnetwork (RNN) models, which do not. Both classes of mod-els correctly predicted increased difficulty in ambiguous sen-tences compared to controls, suggesting that the syntactic rep-resentations induced by RNNs are sufficient for this purpose.At the same time, surprisal estimates derived from all mod-els systematically underestimated the magnitude of the effect,and failed to predict the difference between easier (NP/S) andharder (NP/Z) ambiguities. This suggests that it may not bepossible to reduce garden path effects to predictability", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [ { "word": "self-paced reading; garden path; neural networks" } ], "section": "Publication-based-Talks", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/7mg5442r", "frozenauthors": [ { "first_name": "Marten", "middle_name": "", "last_name": "van Schijndel", "name_suffix": "", "institution": "John Hopkins", "department": "" }, { "first_name": "Tal", "middle_name": "", "last_name": "Linzen", "name_suffix": "", "institution": "John Hopkins", "department": "" } ], "date_submitted": null, "date_accepted": null, "date_published": "2018-01-01T18:00:00Z", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/28176/galley/17835/download/" } ] }