{"pk":49450,"title":"Content-agnostic online segmentation as a core operation","subtitle":null,"abstract":"We approach the problem of explaining segmentation --- the human capacity to partition input streams into representations of appropriate form and content for efficient downstream processing --- by exploring a theoretically minimalistic and computationally plausible account of phoneme-to-word chunking. Through computational models, mathematical proofs, algorithm design, and observer model simulations in two languages, we suggest that online segmentation can be guided by content-agnostic properties of internal memory structures (i.e., lexicality and length type frequency).\nOur theoretical and empirical findings point to a formal link between such properties with practical performance benefits. Together, these contributions make progress on a fully explicit computational- and algorithmic-level account with plausible implementational-level primitives.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"Artificial Intelligence; Cognitive Neuroscience; Computer Science; Linguistics; Computational Modeling; Mathematical modeling"}],"section":"Papers with Poster Presentation","is_remote":true,"remote_url":"https://escholarship.org/uc/item/5c62p8tz","frozenauthors":[{"first_name":"Federico","middle_name":"","last_name":"Adolfi","name_suffix":"","institution":"ESI Neuroscience, Max Planck Society","department":""},{"first_name":"Yue","middle_name":"","last_name":"Sun","name_suffix":"","institution":"Ernst StrŸngmann Institute for Neuroscience","department":""},{"first_name":"David","middle_name":"","last_name":"Poeppel","name_suffix":"","institution":"New York University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2025-01-01T10:00:00-08:00","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/49450/galley/37412/download/"}]}