Learning phonetically and phonologically natural classes through constraint indexation

Phonological processes tend to be defined over natural classes (Chomsky & Halle 1968), but there are some arbitrary and language-specific aspects to class behaviour (e.g., Mielke 2004). This paper shows that it is possible to implement a procedure of finding language specific natural classes using contrast detection (Dresher 2014, Sanstedt 2018), but in standard OT with domain-general methods. Three toy languages are constructed, based on those in Prickett & Jarosz (2021), in which /e/ raises to [i] in the presence of a high vowel and in which /s/ palatalizes to [ʃ] before [i]. In one language, raising feeds palatalization (transparent); in the second, raising counterfeeds palatalization (opaque); in the third, raising applies transparently, but only in certain morphemes (lexically specific). All three languages are learned with a version of Round’s (2017) learner that learns indexed constraints (Pater 2000) that are attached to specific segments in morphemes rather than entire morphemes (cf. Nazarov 2021). This learner is able to find appropriate natural classes for these data, both phonetic natural classes (=traditional natural classes) and what I call phonologically natural classes (classes defined by having certain phonetic properties and undergoing a range of phonological processes), showing the feasibility of this approach.