Dissertation - Michael Becker

contrasted with general-purpose statistical learners that can learn any robust distributionalgeneralization, as discussed in §2.5.2.4 Analysis with cloned constraintsTurkish speakers evidence a detailed knowledge of trends in their lexicon that regulatethe choice of alternation or non-alternation of stem-final stops. Furthermore, speakers arebiased by Universal Grammar to learn only lexical trends that can be captured in termsof cross-linguistically observed interactions between phonological elements. This sectionshows how an OT-based model can be used to learn the trends that humans learn. The modelreads in the lexicon of Turkish and projects a probabilistic grammar from it, a grammarthat can in turn be used to derive novel words in a way that correlates with the experimentalresults shown in §2.3.Given a stop-final novel noun and asked to choose a possessive form for it, Turkishspeakers consult a subset of their lexicon: For instance, given the noun dap, speakersidentify it as a mono-syllabic p-final simplex-coda noun, and they compare it to the othermono-syllabic p-final simplex-coda nouns in their lexicon. If they have 30 such nouns,of which 8 alternate and 22 don’t alternate, as in TELL, then the likelihood that dap willexhibit a voicing alternation is 8 out of 30, or 27%.In other words, Turkish speakers partition their lexicon based on phonological principles.The mass of stop-final nouns is partitioned by the size of each noun (mono- vs. polysyllabic),by the place of articulation of the final stop (p, t, Ù, k), and by the complexityof the final coda, and within each such group, alternating nouns are separated from nonalternatingnouns. This creates a total of 2 * 4 * 2 * 2 = 32 partitions. Nouns that don’t endin a stop are all lumped together in the “elsewhere” partition.Constraint cloning is a mechanism for partitioning the lexicon and listing the wordsthat belong in each partition. The partitions are defined by the set of universal constraints42