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

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... udents, 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.