全球學習漢語的人數已超過四千萬，而這個數字還在持續增加當中。華語文能力測驗也逐漸成為世界知名的語文能力測驗，但是台灣的華語文測驗發展較中國大陸的漢語水平考試HSK晚十五年。然而，拜科技所賜，現今我們可以利用電腦輔助完成這種耗時耗力的工作。華語文電腦出題目前還只是剛起步的研究領域，英文詞彙語法(Multiple-choice cloze)電腦出題有很多方法值得華語文詞彙語法電腦出題借鏡，但用來篩選候選誘答選項的方法，卻無法直接套用到華語文詞彙語法之電腦出題上。本研究目的是設計一個方法來計算華語文詞彙語法之誘答選項的正答力，解決篩選候選誘答選項的問題，並以Google為N-gram的count值來源。本研究參考Markov chain及Katz Backoff演算法來設計本研究的方法，並以台灣華語文能力測驗TOP-Huayu的詞彙語法題100題評估本方法的準確度。 Over 40 million people are learning the Chinese language and interest keeps growing. The Chinese proficiency test becomes progressively a famous language test in the world. The first formal Chinese proficiency test by Taiwan comes fifteen years after the Hanyu Shuiping Kaoshi (HSK) by China. Thanks to computer technology, we can generate the test by a computer easily. Computer-assisted Chinese language testing generator is still a brand new field of research. There are many methods from English multiple-choice cloze generator can be refer to Chinese multiple-choice cloze generator except the method for filtering unsuitable candidate distractors. The purpose of this study is to design a new method to compute correctness of candidate distractors. This study solves the problem of filtering unsuitable candidate distractors. The N-gram count value of this method is from Google web search. The accuracy of this method is assessed by one hundred Chinese multiple-choice cloze questions of TOP-Huayu.
