An SVM-Based Mandarin Pronunciation Quality Assessment System

作者：Ge Fengpei^*; Pan Fuping; Liu Changliang; Dong Bin; Chan Shui duen; Zhu Xinhua; Yan Yonghong

来源：6th International Symposium on Neural Networks, 2009 to 2009.

• SVM
• Pronunciation Quality Assessment
• CALL
• Speaker Adaptation
• Speech Recognition

This paper presents our Mandarin pronunciation quality assessment system for the examination of Putonghua Shuiping Kaoshi (PSK) and investigates a novel Support Vector Machine (SVM) based method to improve its assessment accuracy. Firstly, an selective speaker adaptation module is introduced, in which we select well pronounced speech from results of the first-pass automatic pronunciation scoring as the adaptation data, and adopt Maximum Likelihood Linear Regression to update the acoustic model (AM). Then, compared with the traditional triphone based AM, the monophone based AM is studied. Finally, we propose a new method of incorporating all kinds of posterior probabilities using SVM classifier. Experimental results show that the average correlation coefficient between machine and human scores is improved from 83.72% to 85.48%. It suggests that the two methods of selective speaker adaptation and multi-model combination using SVM are very effective to improve the accuracy of pronunciation quality assessment.

• 出版日期2009
• 单位中国科学院声学研究所