Abstract: To solve the limitation that the traditional K-nearest neighbor algorithm may divide a sample to a wrong class, the concept of fuzzy class membership function is used to improve the K-nearest neighbor algorithm. The experiment in speech emotion recognition is implemented and the results show the effectiveness of the improved algorithm.