Combining Lexical and Grammatical Features to Improve Readability Measures for First and Second Language Texts
Combining Lexical and Grammatical Features to Improve Readability Measures for First and Second Language Texts
复制标题
结合词汇和语法特征来提高第一和第二语言文本的可读性测量
DOI：
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发表时间：
2007
期刊：
影响因子：
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通讯作者：
M. Eskénazi
中科院分区：
文献类型：
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作者：
Michael Heilman;Kevyn Collins;Jamie Callan;M. Eskénazi
这项工作评估了一个系统，使用插值预测的阅读难度的基础上的词汇和语法功能。相结合的方法相比，个别的语法和语言建模为基础的方法。虽然基于词汇的语言建模方法优于基于语法的方法，但是可以使用置信度分数将基于语法的预测与基于词汇的预测相结合，以产生对第一和第二语言文本的阅读难度的更准确的预测。研究结果还表明，语法特征在第二语言可读性中可能比在第一语言可读性中起更重要的作用。
This work evaluates a system that uses interpolated predictions of reading difficulty that are based on both vocabulary and grammatical features. The combined approach is compared to individual grammar- and language modeling-based approaches. While the vocabulary-based language modeling approach outperformed the grammar-based approach, grammar-based predictions can be combined using confidence scores with the vocabulary-based predictions to produce more accurate predictions of reading difficulty for both first and second language texts. The results also indicate that grammatical features may play a more important role in second language readability than in first language readability.