How the input shapes the acquisition of verb morphology: Elicited production and computational modelling in two highly inflected languages.

Affiliation

University of Manchester, UK; ESRC International Centre for Language and Communicative Development (LuCiD), UK. Electronic address: [Email]

Abstract

The aim of the present work was to develop a computational model of how children acquire inflectional morphology for marking person and number; one of the central challenges in language development. First, in order to establish which putative learning phenomena are sufficiently robust to constitute a target for modelling, we ran large-scale elicited production studies with native learners of Finnish (N = 77; 35-63 months) and Polish (N = 81; 35-59 months), using a novel method that, unlike previous studies, allows for elicitation of all six person/number forms in the paradigm (first, second and third person; singular and plural). We then proceeded to build and test a connectionist model of the acquisition of person/number marking which not only acquires near adult-like mastery of the system (including generalisation to unseen items), but also yields all of the key phenomena observed in the elicited-production studies; specifically, effects of token frequency and phonological neighbourhood density of the target form, and a pattern whereby errors generally reflect the replacement of low frequency targets by higher-frequency forms of the same verb, or forms with the same person/number as the target, but with a suffix from an inappropriate conjugation class. The findings demonstrate that acquisition of even highly complex systems of inflectional morphology can be accounted for by a theoretical model that assumes rote storage and phonological analogy, as opposed to formal symbolic rules.

Keywords

Computational modelling,Cross-linguistic,Elicited production,Language acquisition,Morphology,Neural networks,Verb marking,

OUR Recent Articles