A new formant feature and its application in Mandarin vowel pronunciation quality assessment

作者：Lu Xiao-chun^*; Pan Fu-ping; Yin Jun-xun; Hu Wei-ping

来源：Journal of Central South University, 2013, 20(12): 3573-3581.

DOI：10.1007/s11771-013-1883-2

• computer assisted language learning
• speech recognition
• Gaussian mixture model
• formant
• Gabor feature
• neural network

In order to improve the Mandarin vowel pronunciation quality assessment, a novel formant feature was proposed and applied to formant classification for Chinese Mandarin vowel pronunciation quality evaluation. Formant candidates of each frame were plotted on the time-frequency plane to form a bitmap, and its Gabor feature was extracted to represent the formant trajectory. The feature was then classified by using GMM model and the classification posterior probability was mapped to pronunciation quality grade. The experiments of comparing the Gabor transformation based formant trajectory feature with several other kinds of traditionally used features show that with this method, a human-machine scoring correlation coefficient (CC) of 0.842 can be achieved, which is better than the result of 0.832 by traditional speech recognition techniques. At the same time, considering that the long-term information of formant classification and the short-term information of speech recognition technique are complementary to each other, it is investigated to combine their results with linear or nonlinear methods to further improve the evaluation performance. As a result, experiments on PSK show that the best CC of 0.913, which is very close to the correlation of inter-human rating of 0.94, is gotten by using neural network.

• 出版日期2013-12
• 单位广西师范大学; 中国科学院声学研究所; 华南理工大学