Titlebook: Automated Grammatical Error Detection for Language Learners; Claudia Leacock,Martin Chodorow,Joel Tetreault Book 2010 Springer Nature Swit

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Special Problems of Language Learners,ommas and semicolons, to confuse homophones, and to write run-on sentences. But language learners also make errors that occur comparatively infrequently in writing by native speakers. This is especially true for errors where usage is guided by complex rules that interact with one another, or where n

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Language Learner Data,ived in electronic form. Currently, however, a number of corpora are being developed, some of considerable size, that contain rich error annotations. These corpora can be used for a number of purposes such as error analysis and studies of the influence of L1 on learner errors. And, of course, these

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Evaluating Error Detection Systems,her NLP areas, grammatical error detection does not have a shared task/repository to establish agreed upon standards for evaluation (and annotation). For example, SensEval provides researchers with annotated corpora for word sense disambiguation, where any researcher can download training and test d

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Conclusion,e introduction, we noted that this an exciting area of research because there is the potential for real impact given the vast number of people learning another language and because there is no shortage of interesting problems that need to be solved.

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Paul L. Kaufman MD, PhD,B’Ann True Gabeltoach, the context of a word’s usage is seen as crucially important in determining the word’s meaning. This view underlies Firth’s now-famous dictum that “you shall know a word by the company it keeps”.