PRIMIR: A Developmental Framework of Infant Speech Processing

Abstract

Over the past few years, there has been an increasing emphasis on studying the link between infant speech perception and later language acquisition. This research has yielded some seemingly contradictory findings: In some studies infants appear to use phonetic and indexical detail that they fail to use in other studies. In this article we present a new, unified framework for accounting for these divergent findings. PRIMIR (a developmental framework for Processing Rich Information from Multidimensional Interactive Representations) assumes there is rich information available in the speech input and that the child picks up and organizes this information along a number of multidimensional interactive planes. Use of this rich information depends on the joint activity of 3 dynamic filters. These filters-the initial biases, the developmental level of the child, and requirements of the specific language task the child is facing-work together to differentially direct attention to 1 (or more) plane. In this article we outline the contradictory data that need to be explained, elucidate PRIMIR, including its underlying assumptions and overall architecture, and compare it to existing frameworks. We conclude by presenting core predictions of PRIMIR.