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      Learning opacity in Stratal Maximum Entropy Grammar

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          Abstract

          Opaque phonological patterns are sometimes claimed to be difficult to learn; specific hypotheses have been advanced about the relative difficulty of particular kinds of opaque processes (Kiparsky 1971, 1973), and the kind of data that will be helpful in learning an opaque pattern (Kiparsky 2000). In this paper, we present a computationally implemented learning theory for one grammatical theory of opacity: a Maximum Entropy version of Stratal OT (Berm\'udez-Otero 1999, Kiparsky 2000), and test it on simplified versions of opaque French tense-lax vowel alternations and the opaque interaction of diphthong raising and flapping in Canadian English. We find that the difficulty of opacity can be influenced by evidence for stratal affiliation: the Canadian English case is easier if the learner encounters application of raising outside the flapping context, or non-application of raising between words (i.e., <life> with a raised vowel; <lie for> with a non-raised vowel).

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          The Place of Variation in Phonological Theory

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            A Phonological Dilemma in Canadian English

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              Schwa and the loi de position in Southern French

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                Author and article information

                Journal
                2017-03-07
                Article
                1703.02517
                227558cf-3dff-4315-b495-9c6fe72d9d71

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

                History
                Custom metadata
                23 pages; to appear in Phonology; pre-publication version
                cs.CL

                Theoretical computer science
                Theoretical computer science

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