Syllables, Morphemes and Bayesian Computational Models of Acquiring a Word Grammar

29th Annual Conference of the Cognitive Science Society

C¸ag˘rı C¸o¨ltekin ; Cem Bozs¸ahin

PID  :  122813

来源: CEUR

【 摘 要 】

We report a computational study on the CHILDES database for learning a word grammar of Turkish nouns. The syllablebased model converges to a morphemebased model in terms of over laps in the set of lexical hypotheses. Morphology is a hidden variable in all models, and the search problem for hypotheses is narrowed down by a probabilistic conception of universal grammar a` la Combinatory Categorial Grammar. The conver gence of the syllable model suggests that morphemehood can be an emergent computational property.