Abstract
The aim of this study is to investigate how typological variations in loanword adaptation arise out of phonotactic conspiracy based on quantitative modeling. The data set of ill-formed sound sequences, in particular [ju, wi] into Chinese, was examined using dictionary corpora. It was observed that there are four types of repair strategies to obey backness harmony: epenthesis, deletion, change and coalescence. Two theoretical approaches were taken from a statistical and a phonological angle. First, the effect of the syllable structure upon repair choice was measured by means of generalized linear modeling. The best model predicted that the source syllable without nasal coda tends towards epenthesis, that the source syllable with onset prefers deletion, and that the source syllable with nasal coda and without onset favors change. Second, a detailed comparison was made among weighted-constraint models generated by Harmonic Grammar (Hayes & Boersma) and Optimality Theory (Boersma). A significant improvement in accuracy is found with grammar learning in the model of Stochastic OT in a cross-validation. These results indicate that it is possible to resolve too-many-solutions by providing loanword data with lexical variation, suggesting that Stochastic OT is better than Noisy HG because it adequately reflects distributional asymmetries.
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