Morphology in a Parallel, Distributed, Interactive Architecture of Language Production

The competition-compensation account of developmental language disorder

Children with developmental language disorder (DLD) regularly use the bare form of verbs (e.g., dance) instead of inflected forms (e.g., danced). We propose an account of this behavior in which processing difficulties of children with DLD disproportionally affect processing novel inflected verbs in their input. Limited experience with inflection in novel contexts leads the inflection to face stronger competition from alternatives. Competition is resolved through a compensatory behavior that involves producing a more accessible alternative: in English, the bare form. We formalize this hypothesis within a probabilistic model that trades off context-dependent versus independent processing. Results show an over-reliance on preceding stem contexts when retrieving the inflection in a model that has difficulty with processing novel inflected forms. We further show that following the introduction of a bias to store and retrieve forms with preceding contexts, generalization in the typically developing (TD) models remains more or less stable, while the same bias in the DLD models exaggerates difficulties with generalization. Together, the results suggest that inconsistent use of inflectional morphemes by children with DLD could stem from inferences they make on the basis of data containing fewer novel inflected forms. Our account extends these findings to suggest that problems with detecting a form in novel contexts combined with a bias to rely on familiar contexts when retrieving a form could explain sequential planning difficulties in children with DLD. RESEARCH HIGHLIGHTS: Generalization difficulties with inflectional morphemes in children with Developmental Language Disorder arise from these children's limited experience with novel inflected forms. Limited experience with a form in novel contexts could lead to a storage bias where retrieving a form often requires relying on familiar preceding stems. While generalization in typically developing models remains stable across a range of model parameters, certain parameter values in the impaired models exaggerate difficulties with generalization. Children with DLD compensate for these retrieval difficulties through accessibility-driven language production: they produce the most accessible form among the alternatives.