AUTOMATIC IDENTIFICATION OF VIETNAMESE DIALECTS
Pham Ngoc Hung, Trịnh Văn Loan, Nguyễn Hồng Quang · Journal of Computer Science and Cybernetics · 2016
The dialect identification was studied for many languages over the world nevertheless the research on signal processing for Vietnamese dialects is still limited and there were not many published works. There are many different dialects for Vietnamese. The influence of dialectal features on speech recognition systems is important. If the information about dialects is known during speech recognition process, the performance of recognition systems will be better because the corpus of these systems is normally organized according to different dialects. This paper will present the combination of MFCC coefficients and fundamental frequency features of Vietnamese for dialectal identification based on GMM. The experiment result for the dialect corpus of Vietnamese shows that the performance of dialectal identification is increased from 59% for the case using only MFCC coefficients to 71% for the case using MFCC coefficients and the information of fundamental frequency.