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Seq2Seq Models with Dropout can Learn Generalizable Reduplication
Natural language reduplication can pose a challenge to neural models of language, and has been argued to require variables (Marcus et al., 1999).
Learning opacity in Stratal Maximum Entropy Grammar
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).
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