Combining Lexical and Grammatical Features to Improve Readability Measures for First and Second Language Texts.-paper

阿新 • • 發佈：2018-12-23

http://www.aclweb.org/anthology/N07-1058

Volume:Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Proceedings of the Main Conference
Authors:Michael Heilman | Kevyn Collins-Thompson | Jamie Callan | Maxine Eskenazi
Month:April
Year:2007
Venues:NAACL | HLT

資料不公開

1、introduction

L1英語學習者而言，英語水平很高的時候的語法能力其實和開始學英語的時候差不多，因為他們的語法是在使用中互動中學會的，而L2是在課本中學會的，所以L2高階學習者的語法可能不可強。所以grammer對於L2的readability的預測和評估很重要，比如動詞時態、被動時態等。

2、language model readability prediction for first language texts

統計語言模型比傳統公式的好處：

1）短文字和web文字上的準確率更高

2）給出概率分佈而不是一個預測值

3）語言模型可以提供更多關於文字中單詞相對難度的資料

我們的統計模型用的是多項式貝葉斯分佈（就跟上一篇paper一樣）

雖然unigram是weak model，但是會比tri、bi這種更復雜的模型要求更少的資料集

3、grammatical construction readability prediction for second language texts

3.1 features for grammer-based prediction

斯坦福parser用來產生constituent structure trees

PCFG scores可以用來過濾掉預料中有問題的文字

預設訓練集是Penn Treebank來parser，因為該文字和L2學習者的閱讀材料是相近的

Combining Lexical and Grammatical Features to Improve Readability Measures for First and Second Language Texts.-paper

http://www.aclweb.org/anthology/N07-1058 Volume:Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Comp

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Combining Lexical and Grammatical Features to Improve Readability Measures for First and Second Language Texts.-paper

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