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中文摘要：
本文研究了英语篇章朗读的计算机自动评分。本文根据人工评分的角度和准则，用语音识别技术分析语音，提取一系列评价特征，包括朗读完整度特征、发音准确度特征、流利度特征，然后通过SVM回归把这些评价特征映射为质量分数。在对4000名中学生的英语水平自动测试中，用3200名学生的人工评分训练系统，对其余800名学生的机器自动测试取得分差为1．18的良好结果，而专家评分与参考评分的平均分差为1.31。实验表明该项技术已达到实用化水平。
英文摘要：
In this paper we studied the computer automatic scoring for English discourse oral reading. According to the view and guidelines of manual scoring, we analyzed the voices from oral reading with speech recognition technology, and extracted the series of features including reading completeness features, pronunciation accuracy features and fluency features for evaluation. We mapped these features to scores by SVM regression. In the testing of English discourse oral reading for 4000 middle school students, in which the materials of 3200 students were used to train and the rest of 800 students to test, we got a good result that the difference between average machine score and reference score is 1.18, while the difference between average human score and reference score is 1.31. The experience result shows this system can be used in practice.
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