Title: Acoustic analysis of the vowel system in Hotan dialect and its contribution to dialect recognition of Uyghur dialects

SUN Jie; WUSHOUER Silamu; REYIMAN Turson; ZHANG Jingjing;

Affiliation(s): College of Information Science and Engineering, Xinjiang University; Department of Physics, Changji University;

Abstract: Based on the actual needs of speech application research such as speech recognition and voiceprint recognition, the acoustic characteristics and recognition of Hotan dialect were studied for the first time. Firstly, the Hetian dialect voice was selected for artificial multi-level annotation, and the formant, duration and intensity of the vowel were analyzed to describe statistically the main pattern of Hetian dialect and the pronunciation characteristics of male and female. Then using the analysis of variance and nonparametric analysis to test the formant samples of the three dialects of Uygur language, the results show that there are significant differences in the formant distribution patterns of male vowels, female vowels and whole vowels in the three dialects. Finally, the GUM-UBM (Gaussian Mixture Model-Universal Background Model), DNN-UBM (Deep Neural Networks-Universal Background Model) and LSTM-UBM (Long Short Term Memory Network-Universal Background Model) Uyghur dialect recognition models are constructed respectively. Based on the Mel-frequency cepstrum coefficient and its combination with the formant frequency for the input feature extraction, the contrastive experiment of dialect i-vector distinctiveness is carried out. The experimental results show that the combined features of the formant coefficients can increase the recognition of the dialect, and the LSTM-UBM model can extract more discriminative dialects than the GMM-UBM and DNN-UBM.