关键词: 汉语方言辨识, 韵律特征, I-vector, 特征融合

Abstract: A new method of Chinese dialects identification based on Identity vector（I-vector） combined with prosodic information is proposed. The high-dimensional super-vector is mapped to a low-dimensional I-vector representation by Total Variability（TV） model. Channel compensation and feature dimension reduction are also performed. Chinese is a typical language with a tone and Chinese dialects have obvious differences among rhythm, stress and other rhythmic structure. The serial fusion of I-vectors with global prosodic information can improve the distinguishability of Chinese dialects effectively. The Equal Error Rate（EER） using fusion strategy of five Chinese dialects and Mandarin is 8.01%, which is 56.2% lower than the Gaussian Mixture Model-Universal Background Model（GMM-UBM） method. The experimental results show that the I-vector method fusing global prosodic information can improve the Chinese dialects identification accuracy effectively.

Key words: Chinese dialects identification, prosodic features, I-vector, features fusion