Speaker recognition using fuzzy C-mean clustering algorithm and vector-quantization(VQ) algorithm

In this paper, an efficient method for speaker recognition-the combination of VQ (Vector-Quantization) algorithm with fuzzy C-mean clustering algorithm is proposed. This algorithm extracts 12th order LPC cepstrum coefficients from speech signals and makes them the marker of those samples, which will be classified. At first, codebooks which can represent those feature parameters of each speaker are figured out, and used as the clustering centers of speaker recognition. Finally, all speakers feature parameters are identified from each other with fuzzy C-mean clustering algorithm in which the clustering centers are these codebooks which has been obtained using VQ algorithm. With relatively less feature parmeters and simpler computation, the proposed algorithm has a higher recognition rate compared with VQ algorithm.