Computational models of child language learning: an introduction.

This special issue showcases recent work on the computational modeling of child language acquisition. Together, these nine papers provide testimony to the scientific value of corpus-driven computational modeling. Each of the papers presents a clear, mechanistic model that can be tested, refined or rejected on the basis of publicly available data and/or replicable experiments. However, for many readers, the multiple formalisms and technicalities involved in this type of work can serve as barriers to evaluating the nature of the contributions being made. Therefore, it is my goal in this introduction to summarize what I see as the important take-home messages delivered by each of the nine projects. Hopefully, this overview will encourage the reader to turn then to the details of each of the nine contributions.