Proceedings of the Annual Meeting of the Cognitive Science Society

Language acquisition is a significant developmental process children undertake automatically but is only partially un-derstood. Though researchers have long debated the influence of internal knowledge and external stimuli in languageacquisition, both features are required for this process. External stimuli are dominated by child-directed speech for thefirst few years of life. Accordingly, the role of child-directed speech (CDS) in early language acquisition continues toattract cognitive and developmental researchers. Here, we use statistical and computational tools from Automatic SpeechRecognition (ASR) and Network Science to explore the statistical nature of CDS. In particular, we examine CDS usingtwo complementary computational approaches: a bottom-up approach using ASR as a representation of auditory process-ing, and a top-down approach using networks to represent semantic and syntactic knowledge. Exploring CDS with bothmethods offers the unique opportunity to model the role of CDS in language acquisition from a more holistic perspective.