An “AI readability” Formula for French as a Foreign Language
An “AI readability” Formula for French as a Foreign Language
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法语作为外语的“人工智能可读性”公式
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发表时间：
2012
期刊：
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通讯作者：
Cedric Fairon
中科院分区：
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作者：
Thomas François;Cedric Fairon
本文提出了一个新的法语作为外语的可读性公式，该公式依赖于46个文本特征，这些特征代表了法语作为外语的词汇、句法和语义层面以及一些特定的fi城市。我们报告了几种特征选择技术和各种学习算法之间的比较。我们最好的基于支持向量机的模型，sig-nifi比以前的公式有更好的性能。我们还发现，与之前一些关于英语作为fi第一语言的可读性研究相比，语义特征在我们的情况下表现得很差。
This paper present a new readability formula for French as a foreign language (FFL), which relies on 46 textual features representative of the lexical, syntactic, and semantic levels as well as some of the specificities of the FFL context. We report comparisons between several techniques for feature selection and various learning algorithms. Our best model, based on support vector machines (SVM), sig-nificantly outperforms previous FFL formulas. We also found that semantic features behave poorly in our case, in contrast with some previous readability studies on English as a first language.