Publications

Abstract

Repetition appears to be part of error correction and action preparation in all domains that involve producing an action sequence. The present work contends that the ubiquity of repetition is due to its role in resolving a problem inherent to planning and retrieval of action sequences: the Problem of Retrieval. Repetitions occur when the production to perform next is not activated enough to be executed. Repetitions are helpful in this situation because the repeated action sequence activates the likely continuation. We model a corpus of natural speech using a recurrent network, with words as units of production. We show that repeated material makes upcoming words more predictable, especially when more than one word is repeated. Speakers are argued to produce multiword repetitions by using backward associations to reactivate recently produced words. The existence of multiword repetitions means that speakers must decide where to reinitiate execution from. We show that production restarts from words that have seldom occurred in a predictive preceding-word context and have often occurred utterance-initially. These results are explained by competition between preceding-context and top-down cues over the course of language learning. The proposed theory improves on structural accounts of repetition disfluencies, and integrates repetition disfluencies in language production with repetitions observed in other domains of skilled action.

Abstract

Children with developmental language disorder (DLD) regularly use the base form of verbs (e.g., dance) instead of inflected forms (e.g., danced). We propose an account of this behavior in which children with DLD have difficulty processing novel inflected verbs in their input. This leads the inflected form to face stronger competition from alternatives. Competition is resolved by the production of a more accessible alternative with high semantic overlap with the inflected form: in English, the bare form. We test our account computationally by training a nonparametric Bayesian model that infers the productivity of the inflectional suffix (-ed). We systematically vary the number of novel types of inflected verbs in the input to simulate the input as processed by children with and without DLD. Modeling results are consistent with our hypothesis, suggesting that children’s inconsistent use of inflectional morphemes could stem from inferences they make on the basis of impoverished data.