Abstract: Type-2 fuzzy C-means clustering algorithm is applied to solve the digital audio signal classification problem, and jumping genes genetic algorithm is used to optimized the initial fuzzy model which is obtained by the clustering algorithm. At last, the optimized fuzzy rule base is simplified by the vector similarity measure, and the final fuzzy classifier model is obtained. Compared with conventional type-1 fuzzy sets, type-2 fuzzy sets can handle more uncertain information. Type-2 fuzzy C-means clustering algorithm has more accurate results for sample sets whose samples distribute uneven and structures are irregular. The experiment results illustrate that the audio classifier which is based on the type-2 fuzzy C-means clustering algorithm has more precise results than the classifiers which are based on the type-1 fuzzy C-means clustering algorithm.