Study on a Speech Learning Approach Based on Interval Support Vector Regression

摘要：

In this paper an interval regression model has been established to cope with the situation that the input training data is accurate while the output one is interval. And the model has been applied in English speech learning system to predict the credible interval of correct speech and then give a correct judgment for the learners. Experimental data show that the new model reduces the workload of fuzzy prediction and has good accuracy, so it can be effective in speech learning system.

关键词： interval regression SVR speech learning eigenvector eztraction

作者: Peipei Liu

作者单位: Department of Computer North China Electric Power University Baoding, Hebei Province, China

会议类型: 国际会议

会议名称: 第四届国际计算机新科技与教育学术会议(2009 4th International Conference on Computer Science & Education)

会议地点: 南京

会议语种:英文

页码: 1009-1012

在线出版日期: 2009-07-25（万方平台首次上网日期，不代表论文的发表时间）