VIETNAMESE DIALECT IDENTIFICATION ON EMBEDDED SYSTEM

Pham Ngoc Hung; Nguyen Thu Ha; Trinh Van Loan; Vu Xuan Thang; Pham Ngoc Hung; Nguyen Dinh Chien

Pham Ngoc Hung Hung Yen University of Technology and Education
Nguyen Thu Ha Hung Yen University of Technology and Education
Trinh Van Loan Hung Yen University of Technology and Education
Vu Xuan Thang Hung Yen University of Technology and Education
Pham Ngoc Hung Hung Yen University of Technology and Education
Nguyen Dinh Chien Hung Yen University of Technology and Education

Keywords: Vietnamese dialects identification, embedded systems, GMM, MFCC, F0, VDSPEC

Abstract

Many factors affect speech recognition including dialect factors. Vietnamese is a tone language with many different dialects. Therefore, spoken Vietnamese identification is also significantly influenced by dialect. If the information about dialects is known during the speech recognition process, the performance of recognition systems will be better because the corpus of these systems is normally organized according to different dialects. Vietnamese dialect identification has been studied and achieved certain results. Studies are usually carried out on the computer with a powerful computing environment to train models and tests. Embedded devices are being used extensively in practical products, including speech recognition and control, which often have weaker configurations than computers such as slow speed, low memory. Therefore, the implementation of speech recognition on this hardware is more a little difficult. This article presents the results of the research and experiment of Vietnamese dialect identification at embedded systems using the VDSPEC corpus on Raspberry embedded KIT. The study used the GMM identification model with the parameter set of 13 MFCC coefficients and the F0 parameter was standardized according to the average F0 of each sentence, the average recognition rate of dialects is 70%.