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Learning Phonotactic Grammars from Surface Forms Jeffrey Heinz 186-194 (complete pdf) This paper presents an unsupervised batch learning algorithm for phonotactic grammars without a priori Optimality-theoretic constraints (Prince and Smolensky 1993, 2004). The learner generalizes using the notion of natural class and a novel formalization of locality. This learner is applied to three case studies: (1) a language with total ATR harmony (e.g., Kalenjin), (2) a language where the feature ATR is contrastive (e.g., Akan), and (3) a language where the distribution of ATR depends on syllable structure (e.g., Javanese). The learner generalizes successfully in each case from surface forms. This leads to a novel, nontrivial hypothesis with respect to phonotactic constraints: they are all neighborhood-distinct. Published in: Proceedings of the 25th West Coast Conference on Formal Linguistics edited by Donald Baumer, David Montero, and Michael Scanlon Table of contents ISBN 978-1-57473-415-7 library binding vii+461 pages publication date: 2006 published by Cascadilla Proceedings Project, Somerville, MA, USA |