On measuring phonetic precursor robustness: A response to Moreton 2008∗

What factors shape the synchronic typology of sound patterns and how should they be detected? To the extent that the synchronic typology of sound patterns follows from the results of language change, it is commonly, if not implicitly, assumed that analytic and channel biases are two major factors involved in shaping phonological typology (Zuraw 2007; Wilson 2006; Moreton 2008, 2010). Analytic biases are limitations in computation or markedness relations and constraints imposed by the Universal Grammar. An analytic bias might render certain patterns difficult to acquire even from perfect learning data. Channel bias refers to the relative likelihood of phonetic precursor to sound change becoming phonologized into full fledged sound patterns (e.g., Hyman 1976; Ohala 1993; Lindblom et al. 1995; Hume and Johnson 2001; Blevins 2004). This view of phonological typology is motivated by the commonly held assumption that sound patterns and sound changes that recur across unrelated languages originate in properties of human articulatory, perceptual and/or auditory mechanisms (Ohala 1983, 1993; Beddor et al. 2007). Context-induced phonetic variation in speech production and perception is taken to be the phonetic precursors to listener misperceptionbased sound changes. Phonologization refers to this transition of gradient phonetic variation (i.e. intrinsic allophones) becoming entrenched and developing into categorical phonological ∗I have benefitted tremendously from discussion with Sharon Peperkamp and Morgan Sonderegger and comments from the three anonymous reviewers, the associate editors, and the audiences at the Manchester Phonology Meeting in 2009, the Workshop on Computational Modeling of Sound Pattern Acquisition at the University of Alberta, University of Pittsburgh, Michigan State University, and Stony Brook University. Naturally, all errors are my own. This material is based upon work partially supported by the National Science Foundation under Grant No. 0949754. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.