A proposed decision rule for speaker recognition based on fuzzy c-means clustering

In vector quantisation (VQ) based speaker recognition, the minimum overall average distortion rule is used as a criterion to assign a given sequence of acoustic vectors to a speaker model known as a codebook. An alternative decision rule based on fuzzy c-means clustering is proposed in this paper. A set of membership functions associated with vectors for codebooks are defined as discriminant functions and the maximum overall average membership function rule is stated. The theoretical analysis and the experimental results show that this rule can be used in both speaker identification and speaker verification. It is more effective than the minimum overall average distortion rule.