Modeling children’s case marking errors with MOSAIC

Abstract

We present a computational model of early grammatical development which simulates case-marking errors in children’s early multi-word speech as a function of the interaction between a performance-limited distributional analyser and the statistical properties of the input. The model is presented with a corpus of maternal speech from which it constructs a network consisting of nodes which represent words or sequences of words present in the input. It is sensitive to the distributional properties of items occurring in the input and is able to create ‘generative’ links between words which occur frequently in similar contexts, building pseudo-categories. The only information received by the model is that present in the input corpus. After training, the model is able to produce child-like utterances, including case-marking errors, of which a proportion are rote-learned, but the majority are not present in the maternal corpus. The latter are generated by traversing the generative links formed between items in the network.