Automatic Measurement of Syntactic Development in Child Language

Proceedings of the 43rd Annual Meeting of the ACL, pages 197–204, Ann Arbor, June 2005. c⃝2005 Association for Computational Linguistics Automatic Measurement of Syntactic Development in Child Language Kenji Sagae and Alon Lavie Language Technologies Institute Carnegie Mellon University Pittsburgh, PA 15232 {sagae,alavie}@cs.cmu.edu Brian MacWhinney Department of Psychology Carnegie Mellon University Pittsburgh, PA 15232 macw@cmu.edu Abstract To facilitate the use of syntactic infor- mation in the study of child language acquisition, a coding scheme for Gram- matical Relations (GRs) in transcripts of parent-child dialogs has been proposed by Sagae, MacWhinney and Lavie (2004). We discuss the use of current NLP tech- niques to produce the GRs in this an- notation scheme. By using a statisti- cal parser (Charniak, 2000) and memory- based learning tools for classification (Daelemans et al., 2004), we obtain high precision and recall of several GRs. We demonstrate the usefulness of this ap- proach by performing automatic measure- ments of syntactic development with the Index of Productive Syntax (Scarborough, 1990) at similar levels to what child lan- guage researchers compute manually. 1 Introduction Automatic syntactic analysis of natural language has benefited greatly from statistical and corpus-based approaches in the past decade. The availability of syntactically annotated data has fueled the develop- ment of high quality statistical parsers, which have had a large impact in several areas of human lan- guage technologies. Similarly, in the study of child language, the availability of large amounts of elec- tronically accessible empirical data in the form of child language transcripts has been shifting much of the research effort towards a corpus-based mental- ity. However, child language researchers have only recently begun to utilize modern NLP techniques for syntactic analysis. Although it is now common for researchers to rely on automatic morphosyntactic analyses of transcripts to obtain part-of-speech and morphological analyses, their use of syntactic pars- ing is rare. Sagae, MacWhinney and Lavie (2004) have proposed a syntactic annotation scheme for the CHILDES database (MacWhinney, 2000), which contains hundreds of megabytes of transcript data and has been used in over 1,500 studies in child lan- guage acquisition and developmental language dis- orders. This annotation scheme focuses on syntactic structures of particular importance in the study of child language. In this paper, we describe the use of existing NLP tools to parse child language tran- scripts and produce automatically annotated data in the format of the scheme of Sagae et al. We also validate the usefulness of the annotation scheme and our analysis system by applying them towards the practical task of measuring syntactic development in children according to the Index of Productive Syn- tax, or IPSyn (Scarborough, 1990), which requires syntactic analysis of text and has traditionally been computed manually. Results obtained with current NLP technology are close to what is expected of hu- man performance in IPSyn computations, but there is still room for improvement. 2 The Index of Productive Syntax (IPSyn) The Index of Productive Syntax (Scarborough, 1990) is a measure of development of child lan- guage that provides a …

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