Improvements on Mandarin Pronunciation Evaluation

In this paper,PNCC(Power-Normalized Cepstral Coefficients) is introduced into Mandarin pronunciation evaluation system for reducing the impact of background noise.The result shows that the score correlation based on PNCC has been increased by 6.6% compared with classical MFCC.Then,different initial-final acoustic model structures for Chinese syllables are investigated on Mandarin pronunciation evaluation.An initial-medial and final(IMF) modeling is applied,resulting 5.6% reduction of the error rate and an increase of 0.056 score correlation.Finally,the number of states in HMM model is discussed for pronunciation scoring,and some mixed score computing schemes based on either models or scores are proposed.Test results show the score correlation with the experts has been increased by 0.021 and 0.017 respectively.