Lexically Ranked Ocp-place Constraints in Muna

In this paper, we analyze the consonant co-occurrence restrictions in the Austronesian language Muna. As in Arabic and other languages, homorganic segments are underrepresented, particularly ones that are also similar in other ways. However, in Muna [voice] plays an unusually central role in this pattern. We analyze the Muna restrictions within Optimality Theory, using OCP-PLACE constraints relativized to [voice], [continuant], and [sonorant]. We claim that these constraints are ranked according the frequency with which they are violated in the lexicon. Interspersed amongst these OCP-PLACE constraints are lexically specific faithfulness constraints. We show how such a grammar can be used to explain gradient phonological well-formedness judgments; a nonce word is assigned a well-formedness score based on how often it would be parsed faithfully, given its indexation to each of the lexically specific constraints. We also show how a grammar that is sensitive to lexical frequency can be learned using a slightly augmented version of the Biased Constraint Demotion algorithm (Prince and Tesar 2004). Finally, we discuss the similarity avoidance model of Frisch et al. (2004); we find that the Muna data are consistent with some of its claims, but problematic for its basic premise that similarity is mediated by inventory structure. Like many other languages, Muna (van den Berg 1989) has a restriction on the co-occurrence of homorganic consonants within a word, which is observed in the statistical underrepresentation of homorganic consonant pairs in the lexicon. And as in other languages, the strength of this restriction differs according to place of articulation, and according to how similar the consonants are in other respects. Muna is unique, however, in the degree to which [voice] agreement correlates with the underrepresentation of homorganic pairs. We advance an analysis of the Muna data in terms of OCP-PLACE constraints (McCarthy 1988) that are relativized to place of articulation and other features, including [voice] (cf. Padgett 1995). We propose a ranking of these constraints that corresponds to the degree to which they are obeyed in the lexicon. We also analyze the Muna data in terms of Frisch, Pierrehumbert and Broe’s (2004) similarity metric. The Muna data are consistent with some aspects of their proposal, but pose a challenge for the central claim that differences in inventory structure are responsible for differences in similarity between consonant pairs that have the same number of features in common. Differences in inventories can explain neither the differences across place of articulation in Muna, nor the differences in the importance of [voice] agreement between Muna and Arabic. The rest of this paper is structured as follows: In section 1, we discuss the details of the consonant co-occurrence restrictions in Muna. In section 2, we develop an account of these restrictions using OCP-PLACE constraints, and in section 3, we show how this grammar can be learned within a version of the Biased Constraint Demotion Algorithm (Prince and Tesar 2004). Finally, in section 4, we consider the relevance of the Muna data for Frisch et al.’s (2004) similarity based account of consonant co-occurrence patterns.