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