Dialect identification method based on static and dynamic features
YU Feng-qin · Computer Engineering and Applications Journal · 2012
MFCC(Mel Frequence Cepstral Coefficients)only reflects speech static feature so its dialect recognition rate is low, while SDC(Shifted Delta Cepstra)reflects speech dynamic feature because of considering the connections between several speech frames. For combination of static and dynamic features, MFCC and SDC extracted from Mandarin, Shanghai dialect, Cantonese, Minnan dialect are employed as the feature vector with SVM(Support Vector Machine)for the dialect identification, and effects on performance of different parameters for SDC are stud- ied. Simulation results demonstrate that the dialect recognition rate with static and dynamic features can be up to 92.5%, but its increase is based on the cost of the working time.