Abstract

Spectacular progress in the information processing sci- ences (machine learning, wearable sensors) promises to revo- lutionize the study of cognitive development. Here, we anal- yse the conditions under which ’reverse engineering’ lan- guage development, i.e., building an effective system that mimics infant’s achievements, can contribute to our scien- tific understanding of early language development. We argue that, on the computational side, it is important to move from toy problems to the full complexity of the learning situation, and take as input as faithful reconstructions of the sensory signals available to infants as possible. On the data side, accessible but privacy-preserving repositories of home data have to be setup. On the psycholinguistic side, specific tests have to be constructed to benchmark humans and machines at different linguistic levels. We discuss the feasibility of this approach and present an overview of current results.

Description