Computational Analysis of Child Language Transcript Data

Carnegie-Mellon University, Pittsburgh PA

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Abstract

DESCRIPTION (provided by applicant): The Child Language Data Exchange System (CHILDES) Project seeks to broaden and deepen our scientific understanding of language development by providing new ways of analyzing real world face-to-face interactions. The computational tools that were developed in the previous phases of the project now constitute the primary methodological basis for new empirical research on the development of spontaneous use of a first language. This work has examined all aspects of language development, including word learning, sound learning, grammatical development, and communicative development. All of these methods and data sets are provided without charge to researchers. Moreover, the database that has been collected using these tools is now the largest spoken language database available anywhere. However, we can achieve still greater efficiency and analytic precision by building even more powerful computational tools. The next phase of this project will develop new techniques to support analytic methods in the study of language development. These methods include rapid computer-assisted transcription of interactions, automatic analysis of words into their component parts, automatic linkage of words into syntactic structures, a simple user interface for searching for patterns, a system for analyzing links between speech and gesture, web-based support for collaborative commentary between research groups, and methods for moving data between different programs for alternative analyses. In addition, we will promote the use of these programs by constructing new web-based teaching tools, a new user interface, and conducting workshops and presentations at conferences. PUBLIC HEALTH RELEVANCE To help children with language delays and disorders, we need to understand the basic facts about language learning. The CHILDES project does this by allowing rapid searching for developmental patterns across a large database of transcripts from children learning language. These tools can also be applied to other health- related areas, including the study of adult language disorders, such as aphasia and dysarthria.