关键词: LBG算法, 自适应, 梅尔频率倒谱系数（MFCC）, 模糊聚类, 矢量量化

Abstract: In this paper, a self-adaptive fuzzy c-means clustering algorithm is proposed. It is designed to overcome the shortcomings of the traditional LBG vector-quantization algorithm. Experimental results on MFCC quantization show that the proposed algorithm has similar quantization error compared to the classic LBG algorithm while significantly reducing codebook size and memory footprint.

Key words: LBG algorithm, self-adaption, Mel Frequency Cepstrum Coefficient（MFCC）, fuzzy clustering, Vector Quantization（VQ）