Ambridge calls for exemplar-based accounts of language acquisition. Do modern neural networks such as transformers or word2vec -- which have been extremely successful in modern natural language processing (NLP) applications -- count? Although these models often have ample parametric complexity to store exemplars from their training data, they also…

Language is one of the hallmarks of intelligence, demanding explanation in a theory of human cognition. However, language presents unique practical challenges for quantitative empirical research, making many linguistic theories difficult to test at naturalistic scales. Artificial neural network language models (LMs) provide a new tool for studying…

Purpose: In this study, we examined syntactic complexity in the spoken language samples of young adults. Its purpose was to contribute to the expanding knowledge base in later language development and to begin building a normative database of language samples that potentially could be used to evaluate young adults with known or suspected language…

This study focuses on the development of narrative structure and the relationship between narrative productivity and event content. A total of 172 Finnish children aged between four and eight participated. Their picture-elicited narrations were analysed for productivity, syntactic complexity, referential cohesion and event content. Each measure…

Describes the language learning program "Acquire," which is a sample of grammar induction. It is a learning algorithm based on a pattern-matching scheme, using both a positive and negative network to reduce overgeneration. Language learning programs may be useful as tutorials for learning the syntax of a foreign language. (Author/LMO)