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Correcting Serial Grammatical Errors based on N-grams and Syntax

並列摘要


In this paper, we present a new method based on machine translation for correcting serial grammatical errors in a given sentence in learners' writing. In our approach, translation models are generated to translate the input into a grammatical sentence. The method involves automatically learning two translation models that are based on Web-scale n-grams. The first model translates trigrams containing serial preposition-verb errors into correct ones. The second model is a back-off model, used in the case where the trigram is not found in the training data. At run-time, the phrases in the input are matched and translated, and ranking is performed on all possible translations to produce a corrected sentence as output. Evaluation on a set of sentences in a learner corpus shows that the method corrects serial errors reasonably well. Our methodology exploits the state-of-the art in machine translation, resulting in an effective system that can deal with many error types at the same time.

參考文獻


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被引用紀錄


蘇威誌(2011)。一個用於聊天室應用以同音字為基礎的中文文字隱藏技術〔碩士論文,元智大學〕。華藝線上圖書館。https://doi.org/10.6838/YZU.2011.00244

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