Stratification without morphological strata, syllable counting without counts - modelling English stress assignment with Naive Discriminative Learning

Stress position in English words is well-known to correlate with both their morphological properties and their phonological organisation in terms of non-segmental, prosodic categories like syllable and foot structure. While two generalisations capturing this correlation, directionality and strati cation, are well established, the exact nature of the interaction of phonological and morphological factors in English stress assignment is a much debated issue in the literature. The present study investigates if and how directionality and strati cation e ects in English can be learned by means of Naive Discriminative Learning, a computational model that is trained using error-driven learning and that does not make any a-priori assumptions about the higher-level phonological organisation and morphological structure of words. Based on a series of simulation studies we show that neither directionality nor strati cation need to be stipulated as a-priori properties of words or constraints in the lexicon. Stress can be learned solely on the basis of very at word representations. Morphological strati cation emerges as an e ect of the model learning that informativity with regard to stress position is unevenly distributed across all trigrams constituting a word. Morphological a x classes like stress-preserving and stress-shifting a xes are, hence, not prede ned classes but sets of trigrams that have similar informativity values with regard to stress position. Directionality, by contrast, emerges as spurious in our simulations; no syllable counting or recourse to abstract prosodic representations seems to be necessary to learn stress position in English. Support for this research was provided by the Deutsche Forschungsgemeinschaft, grant FOR 2373 peerReviewed unknown