Automated grammatical error detection for language learners

被引:0
|
作者
Leacock C. [1 ]
Chodorow M. [2 ]
Gamon M. [3 ]
Tetreault J. [4 ]
机构
[1] Hunter College and the Graduate Center, City University of New York (CUNY)
[2] Natural Language Processing Group, Microsoft Research
[3] Research and Development Division, Educational Testing Service, Princeton, NJ
来源
关键词
Grammatical error detection; Learner corpora; Linguistic annotation; Statistical natural language processing;
D O I
10.2200/S00275ED1V01Y201006HLT009
中图分类号
学科分类号
摘要
It has been estimated that over a billion people are using or learning English as a second or foreign language, and the numbers are growing not only for English but for other languages as well. These language learners provide a burgeoning market for tools that help identify and correct learners' writing errors. Unfortunately, the errors targeted by typical commercial proofreading tools do not include those aspects of a second language that are hardest to learn. This volume describes the types of constructions English language learners find most difficult - constructions containing prepositions, articles, and collocations. It provides an overview of the automated approaches that have been developed to identify and correct these and other classes of learner errors in a number of languages. Error annotation and system evaluation are particularly important topics in grammatical error detection because there are no commonly accepted standards. Chapters in the book describe the options available to researchers, recommend best practices for reporting results, and present annotation and evaluation schemes. The final chapters explore recent innovative work that opens new directions for research. It is the authors' hope that this volume will contribute to the growing interest in grammatical error detection by encouraging researchers to take a closer look at the field and its many challenging problems. © 2010 by Morgan & Claypool. All rights reserved.
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页码:1 / 134
页数:133
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