CALICO Journal
May 2009 Volume 26, Number 3
Table of Contents
Number of articles: 11
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Judging Grammaticality: Experiments in Sentence Classification
Joachim Wagner, Jennifer Foster & Josef van Genabith
A classifier which is capable of distinguishing a syntactically well formed sentence from a syntactically ill formed one has the potential to be useful in an L2 language-learning context. In this... More
pp. 474-490
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Using Statistical Techniques and Web Search to Correct ESL Errors
Michael Gamon, Claudia Leacock, Chris Brockett, William B. Dolan, Jianfeng Gao, Dmitriy Belenko & Alexandre Klementiev
In this paper we present a system for automatic correction of errors made by learners of English. The system has two novel aspects. First, machine-learned classifiers trained on large amounts of... More
pp. 491-511
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Automatic Detection of Preposition Errors in Learner Writing
Rachele De Felice & Stephen Pulman
In this article, we present an approach to the automatic correction of preposition errors in L2 English. Our system, based on a maximum entropy classifier, achieves average precision of 42% and... More
pp. 512-528
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Annotation of Korean Learner Corpora for Particle Error Detection
Sun-Hee Lee, Seok Bae Jang & Sang-Kyu Seo
In this study, we focus on particle errors and discuss an annotation scheme for Korean learner corpora that can be used to extract heuristic patterns of particle errors efficiently. We investigate ... More
pp. 529-544
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Modifying Corpus Annotation to Support the Analysis of Learner Language
Markus Dickinson & Chong Min Lee
A crucial question for automatically analyzing learner language is to determine which grammatical information is relevant and useful for learner feedback. Based on knowledge about how learner... More
pp. 545-561
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Robo-Sensei's NLP-Based Error Detection and Feedback Generation
Noriko Nagata
This paper presents a new version of Robo-Sensei's NLP (Natural Language Processing) system which updates the version currently available as the software package "ROBO-SENSEI: Personal Japanese... More
pp. 562-579
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Little Things with Big Effects: On the Identification and Interpretation of Tokens for Error Diagnosis in ICALL
Luiz A. Amaral & W Detmar Meurers
Error diagnosis in ICALL typically analyzes learner input in an attempt to abstract and identify indicators of the learner's (mis)conceptions of linguistic properties. For written input, this... More
pp. 580-591
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Mastering Overdetection and Underdetection in Learner-Answer Processing: Simple Techniques for Analysis and Diagnosis
Alexia Blanchard, Olivier Kraif & Claude Ponton
This paper presents a "didactic triangulation" strategy to cope with the problem of reliability of NLP applications for computer-assisted language learning (CALL) systems. It is based on the... More
pp. 592-610
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TechWriter: An Evolving System for Writing Assistance for Advanced Learners of English
Diane M. Napolitano & Amanda Stent
Writing assistance systems, from simple spelling checkers to more complex grammar and readability analyzers, can be helpful aids to nonnative writers of English. However, many writing assistance... More
pp. 611-625
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Computing Accurate Grammatical Feedback in a Virtual Writing Conference for German-Speaking Elementary-School Children: An Approach Based on Natural Language Generation
Karin Harbusch, Gergana Itsova, Ulrich Koch & Christine Kuhner
We built a natural language processing (NLP) system implementing a "virtual writing conference" for elementary-school children, with German as the target language. Currently, state-of-the-art... More
pp. 626-643
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Construction of a Rated Speech Corpus of L2 Learners' Spontaneous Speech
Su-Youn Yoon, Lisa Pierce, Amanda Huensch, Eric Juul, Samantha Perkins, Richard Sproat & Mark Hasegawa-Johnson
This work reports on the construction of a rated database of spontaneous speech produced by second language (L2) learners of English. Spontaneous speech was collected from 28 L2 speakers... More
pp. 662-673