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Morphosyntactic annotation of CHILDES transcripts*

Published online by Cambridge University Press:  25 March 2010

KENJI SAGAE ,
ERIC DAVIS ,
ALON LAVIE ,
BRIAN MACWHINNEY  and
SHULY WINTNER
KENJI SAGAE*
Affiliation:
Institute for Creative Technologies, University of Southern California
ERIC DAVIS
Affiliation:
Language Technologies Institute, Carnegie Mellon University
ALON LAVIE
Affiliation:
Language Technologies Institute, Carnegie Mellon University
BRIAN MACWHINNEY
Affiliation:
Department of Psychology, Carnegie Mellon University
SHULY WINTNER
Affiliation:
Department of Computer Science, University of Haifa, Israel
*
Address for correspondence: Kenji Sagae, USC Institute for Creative Technologies, 13274 Fiji Way, Marina del Rey, CA 90292. e-mail: sagae@usc.edu
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Abstract

Corpora of child language are essential for research in child language acquisition and psycholinguistics. Linguistic annotation of the corpora provides researchers with better means for exploring the development of grammatical constructions and their usage. We describe a project whose goal is to annotate the English section of the CHILDES database with grammatical relations in the form of labeled dependency structures. We have produced a corpus of over 18,800 utterances (approximately 65,000 words) with manually curated gold-standard grammatical relation annotations. Using this corpus, we have developed a highly accurate data-driven parser for the English CHILDES data, which we used to automatically annotate the remainder of the English section of CHILDES. We have also extended the parser to Spanish, and are currently working on supporting more languages. The parser and the manually and automatically annotated data are freely available for research purposes.

Type
Articles
Information
Journal of Child Language , Volume 37 , Special Issue 3: Computational models of child language learning , June 2010 , pp. 705 - 729
Copyright
Copyright © Cambridge University Press 2010

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Footnotes

[*]

We thank Marina Fedner for help with annotation of the English data, and Bracha Nir for help with annotation of the Hebrew data. This research was supported in part by Grant No. 2007241 from the United States–Israel Binational Science Foundation (BSF) and by the National Science Foundation (NSF) under grant IIS-0414630.

References

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