Phonological reanalysis is guided by markedness

The case of Malagasy weak stems

Datos Bibliográficos

ID20399366
AutoresJennifer Kuo (0000-0001-5078-7882, Cornell University, autor de correspondencia)
Año2024
Volumen41
Fecha de publicación2024-01-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaPhonology (JOURNAL)
Identificadores de la revistaISSN: 0952-6757 • E-ISSN: 1469-8188
EditorialCambridge University Press (CUP) (PUBLISHER)
DOI10.1017/s0952675724000174
OpenAlexW4406377833
IdiomaEN
Referencias citadas54

A key goal in phonology is to understand the factors that affect phonological learning. This article addresses the issue by examining how paradigms are reanalysed over time. Malagasy has a class of stems called weak stems, whose final consonants alternate under suffixation. Comparison of historical and modern Malagasy shows that weak stem paradigms have undergone extensive reanalysis in a way that cannot be predicted by the probabilistic distribution of alternants. This poses a problem for existing quantitative models of reanalysis, where reanalysis is always towards the most probable alternant. I argue instead that reanalysis in Malagasy is driven by both distributional factors and a markedness bias. To capture the Malagasy pattern, I propose a maximum entropy learning model, with a markedness bias implemented via the model’s prior probability distribution. This biased model successfully predicts the direction of reanalysis in Malagasy, outperforming purely distributional models

Linguistics · Markedness · Phonology · Probabilistic logic · Computer Science · Language and cultural evolution · Linguistic Variation and Morphology · Philosophy · Phonetics and Phonology Research · Artificial Intelligence