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{ "pk": 49639, "title": "Learn What is Detectable, Detect What is Useful", "subtitle": null, "abstract": "Many computational models of morphology represent complex words by n-grams to account for lexical processing and acquisition. However, while n-gram models are simple and efficient, they are not without problems. From a cognitive perspective, it is unclear how n-gram words are represented in the mental lexicon and how these representations affect language use and acquisition. From a computational perspective, these models are problematic because n-gram representations are often ambiguous and redundant: they make very limited use of distributional information and neglect the role of efficiency and sequential processing in language use and acquisition. In this paper, we present a new computational approach to morphology that is cognitively more plausible than standard n-gram models. By analyzing data from the nominal number system in German, we show that a task-specific algorithm of linear processing guided by the principles of efficiency and reliability outperforms state-of-the-art n-gram models and also makes predictions about lexical processing that are consistent with the judgments of German native speakers in a psycholinguistic experiment.", "language": "eng", "license": { "name": "", "short_name": "", "text": null, "url": "" }, "keywords": [ { "word": "Linguistics; Language acquisition; Learning; Bayesian modeling; Computer-based experiment" } ], "section": "Papers with Poster Presentation", "is_remote": true, "remote_url": "https://escholarship.org/uc/item/1rw3t5zg", "frozenauthors": [ { "first_name": "Sergei", "middle_name": "", "last_name": "Monakhov", "name_suffix": "", "institution": "Friedrich Schiller University Jena", "department": "" }, { "first_name": "Holger", "middle_name": "", "last_name": "Diessel", "name_suffix": "", "institution": "Department of English", "department": "" }, { "first_name": "Brisca", "middle_name": "", "last_name": "Balthes", "name_suffix": "", "institution": "Saarland University", "department": "" } ], "date_submitted": null, "date_accepted": null, "date_published": "2025-01-01T18:00:00Z", "render_galley": null, "galleys": [ { "label": "PDF", "type": "pdf", "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/49639/galley/37601/download/" } ] }