结合语言学特征和自编码器的英语作文自动评分

近年来,越来越多的大规模英语考试采用了自动评分系统.因此,对英语作文自动评分的研究有着非常重要的价值.我们先依据英语作文写作技巧提取了大量语言学特征,再分别使用自编码器,特征值离散化方法对特征进行重构,最后我们使用分层多项模型来输出文章的最终得分.实验表明,该方法能取得很好的预测效果,而且面对不同主题的作文进行预测时也能显示出较好的鲁棒性.相比于传统自动评分方法皮尔森相关系数高出9.7%,具有良好的实际应用价值.

Automatic Essay Scoring Using Linguistic Features and Autoencoder

In recent years, more and more large-scale English tests begin to use the automatic scoring system.Therefore, the research of this system is of great value.In this paper, we first extract a lot of features according to English writing guide.Then we use autoencoder and discretization algorithm to learn a different representation of features.Finally, we use a hierarchical multinomial model to output the final scores of articles.Experimental results indicate that this method not only achieves great performance for those essays of the same topic, but also shows good robustness when predicts essays of different topics.Compared with the traditional automatic score method, our approach achieves higher than 9.7% in term of Pearson Correlation Coefficient, with good practical values.