Accounting for the stochastic nature of sound symbolism using Maximum Entropy model

Kawahara, Shigeto ✉; Katsuda, Hironori; Kumagai, Gakuji

Angol nyelvű Tudományos Szakcikk (Folyóiratcikk)
Megjelent: OPEN LINGUISTICS 2300-9969 5 (1) pp. 109-120 2019
  • SJR Scopus - Language and Linguistics: Q2
Azonosítók
Szakterületek:
    Sound symbolism refers to stochastic and systematic associations between sounds and meanings. Sound symbolism has not received much serious attention in the generative phonology literature, perhaps because most if not all sound symbolic patterns are probabilistic. Building on the recent proposal to analyze sound symbolic patterns within a formal phonological framework (Alderete and Kochetov 2017), this paper shows that MaxEnt grammars allow us to model stochastic sound symbolic patterns in a very natural way. The analyses presented in the paper show that sound symbolic relationships can be modeled in the same way that we model phonological patterns. We suggest that there is nothing fundamental that prohibits formal phonologists from analyzing sound symbolic patterns, and that studying sound symbolism using a formal framework may open up a new, interesting research domain. The current study also reports two hitherto unnoticed cases of sound symbolism, thereby expanding the empirical scope of sound symbolic patterns in natural languages.
    Hivatkozás stílusok: IEEEACMAPAChicagoHarvardCSLMásolásNyomtatás
    2020-12-04 08:43